Index (Encog Core 2.5.3 API)

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actionPerformed(ActionEvent) - Method in class org.encog.util.simple.TrainingDialog: Called when the user clicks the stop button.
ActivationBiPolar - Class in org.encog.engine.network.activation: BiPolar activation function.
ActivationBiPolar() - Constructor for class org.encog.engine.network.activation.ActivationBiPolar: Construct the bipolar activation function.
ActivationCompetitive - Class in org.encog.engine.network.activation: An activation function that only allows a specified number, usually one, of the out-bound connection to win.
ActivationCompetitive() - Constructor for class org.encog.engine.network.activation.ActivationCompetitive: Create a competitive activation function with one winner allowed.
ActivationCompetitive(int) - Constructor for class org.encog.engine.network.activation.ActivationCompetitive: Create a competitive activation function with the specified maximum number of winners.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationBiPolar: Implements the activation function.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationCompetitive: Implements the activation function.
ActivationFunction - Interface in org.encog.engine.network.activation: This interface allows various activation functions to be used with the neural network.
activationFunction(double[], int, int) - Method in interface org.encog.engine.network.activation.ActivationFunction: Implements the activation function.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationGaussian: Implements the activation function.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationLinear: Implements the activation function.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationLOG: Implements the activation function.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationRamp: Implements the activation function.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationSigmoid: Implements the activation function.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationSIN: Implements the activation function.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationSoftMax: Implements the activation function.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationStep: Implements the activation function.
activationFunction(double[], int, int) - Method in class org.encog.engine.network.activation.ActivationTANH: Implements the activation function.
ActivationGaussian - Class in org.encog.engine.network.activation: An activation function based on the gaussian function.
ActivationGaussian(double, double, double) - Constructor for class org.encog.engine.network.activation.ActivationGaussian: Create a gaussian activation function.
ActivationLinear - Class in org.encog.engine.network.activation: The Linear layer is really not an activation function at all.
ActivationLinear() - Constructor for class org.encog.engine.network.activation.ActivationLinear: Construct a linear activation function, with a slope of 1.
ActivationLOG - Class in org.encog.engine.network.activation: An activation function based on the logarithm function.
ActivationLOG() - Constructor for class org.encog.engine.network.activation.ActivationLOG: Construct the activation function.
ActivationRamp - Class in org.encog.engine.network.activation: A ramp activation function.
ActivationRamp(double, double, double, double) - Constructor for class org.encog.engine.network.activation.ActivationRamp: Construct a ramp activation function.
ActivationRamp() - Constructor for class org.encog.engine.network.activation.ActivationRamp: Default constructor.
ActivationSigmoid - Class in org.encog.engine.network.activation: The sigmoid activation function takes on a sigmoidal shape.
ActivationSigmoid() - Constructor for class org.encog.engine.network.activation.ActivationSigmoid: Construct a basic sigmoid function, with a slope of 1.
ActivationSIN - Class in org.encog.engine.network.activation: An activation function based on the sin function.
ActivationSIN() - Constructor for class org.encog.engine.network.activation.ActivationSIN: Construct the sin activation function.
ActivationSoftMax - Class in org.encog.engine.network.activation: The softmax activation function.
ActivationSoftMax() - Constructor for class org.encog.engine.network.activation.ActivationSoftMax: Construct the soft-max activation function.
ActivationStep - Class in org.encog.engine.network.activation: The step activation function is a very simple activation function.
ActivationStep(double, double, double) - Constructor for class org.encog.engine.network.activation.ActivationStep: Construct a step activation function.
ActivationStep() - Constructor for class org.encog.engine.network.activation.ActivationStep: Create a basic step activation with low=0, center=0, high=1.
ActivationTANH - Class in org.encog.engine.network.activation: The hyperbolic tangent activation function takes the curved shape of the hyperbolic tangent.
ActivationTANH() - Constructor for class org.encog.engine.network.activation.ActivationTANH: Construct a basic HTAN activation function, with a slope of 1.
ADALINEPattern - Class in org.encog.neural.pattern: Construct an ADALINE neural network.
ADALINEPattern() - Constructor for class org.encog.neural.pattern.ADALINEPattern
add(double[]) - Method in class org.encog.engine.data.BasicEngineDataSet: Add input to the training set with no expected output.
add(double[], double[]) - Method in class org.encog.engine.data.BasicEngineDataSet: Add input and expected output.
add(EngineData) - Method in class org.encog.engine.data.BasicEngineDataSet: Add a neural data pair to the list.
add(EncogCLDevice, double[], double[]) - Method in class org.encog.engine.opencl.kernels.KernelVectorAdd: Perform the addition.
add(int, int, double) - Method in class org.encog.mathutil.matrices.Matrix: Add a value to one cell in the matrix.
add(Matrix) - Method in class org.encog.mathutil.matrices.Matrix: Add the specified matrix to this matrix.
add(Matrix, Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath: Add two matrixes.
add(int, double) - Method in class org.encog.neural.data.basic.BasicNeuralData: Add a value to the specified index.
add(NeuralData) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Add input to the training set with no expected output.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Add input and expected output.
add(NeuralDataPair) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Add a neural data pair to the list.
add(int, double) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: This will throw an error, as "add" is not supported for bipolar.
add(NeuralData) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Add only input data, for an unsupervised dataset.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Add both the input and ideal data.
add(NeuralDataPair) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Add a data pair of both input and ideal data.
add(NeuralData) - Method in class org.encog.neural.data.csv.CSVNeuralDataSet: Adds are not supported.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.csv.CSVNeuralDataSet: Adds are not supported.
add(NeuralDataPair) - Method in class org.encog.neural.data.csv.CSVNeuralDataSet: Adds are not supported.
add(NeuralData) - Method in class org.encog.neural.data.folded.FoldedDataSet: Not supported.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.folded.FoldedDataSet: Not supported.
add(NeuralDataPair) - Method in class org.encog.neural.data.folded.FoldedDataSet: Not supported.
add(NeuralData) - Method in class org.encog.neural.data.image.ImageNeuralDataSet: Add the specified data, must be an ImageNeuralData class.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.image.ImageNeuralDataSet: Add the specified input and ideal object to the collection.
add(NeuralDataPair) - Method in class org.encog.neural.data.image.ImageNeuralDataSet: Add input and expected output.
add(int, double) - Method in interface org.encog.neural.data.NeuralData: Add a value to the specified index.
add(NeuralData) - Method in interface org.encog.neural.data.NeuralDataSet: Add a NeuralData object to the dataset.
add(NeuralData, NeuralData) - Method in interface org.encog.neural.data.NeuralDataSet: Add a set of input and ideal data to the dataset.
add(NeuralDataPair) - Method in interface org.encog.neural.data.NeuralDataSet: Add a NeuralData object to the dataset.
add(NeuralData) - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Adds are not supported.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Adds are not supported.
add(NeuralDataPair) - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Adds are not supported.
add(NeuralData) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Adding directly is not supported.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Adding directly is not supported.
add(NeuralDataPair) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Adding directly is not supported.
add(NeuralData) - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Not supported.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Not supported.
add(NeuralDataPair) - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Not supported.
add(NeuralData) - Method in class org.encog.neural.data.xml.XMLNeuralDataSet: Adds are not supported, this is a read only data set.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.xml.XMLNeuralDataSet: Adds are not supported, this is a read only data set.
add(NeuralDataPair) - Method in class org.encog.neural.data.xml.XMLNeuralDataSet: Adds are not supported, this is a read only data set.
add(String, EncogPersistedObject) - Method in interface org.encog.persist.EncogCollection: Add an element to the collection.
add(String, EncogPersistedObject) - Method in class org.encog.persist.EncogMemoryCollection: Add an element to the collection.
add(String, EncogPersistedObject) - Method in class org.encog.persist.EncogPersistedCollection: Add an EncogPersistedObject to the collection.
add(Gene) - Method in class org.encog.solve.genetic.genome.Chromosome: Add a gene.
add(Innovation) - Method in class org.encog.solve.genetic.innovation.BasicInnovationList: Add an innovation.
add(Innovation) - Method in interface org.encog.solve.genetic.innovation.InnovationList: Add an innovation.
add(Genome) - Method in class org.encog.solve.genetic.population.BasicPopulation: Add a genome to the population.
add(Genome) - Method in interface org.encog.solve.genetic.population.Population: Add a genome to the population.
add(String, File) - Method in class org.encog.util.http.FormUtility: Add a file to a multipart form.
add(String, String) - Method in class org.encog.util.http.FormUtility: Add a regular text field to either a regular or multipart form.
ADD_NOT_SUPPORTED - Static variable in class org.encog.neural.data.csv.CSVNeuralDataSet: Error message indicating that adds are not supported.
ADD_NOT_SUPPORTED - Static variable in class org.encog.neural.data.folded.FoldedDataSet: Error message: adds are not supported.
ADD_NOT_SUPPORTED - Static variable in class org.encog.neural.data.sql.SQLNeuralDataSet: Error message: adds are not supported.
ADD_NOT_SUPPORTED - Static variable in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Error message: adds are not supported.
ADD_NOT_SUPPORTED - Static variable in class org.encog.neural.data.xml.XMLNeuralDataSet: Error Message: adds are not supported.
addAll(List<? extends Genome>) - Method in class org.encog.solve.genetic.population.BasicPopulation: Add all of the specified members to this population.
addAll(List<? extends Genome>) - Method in interface org.encog.solve.genetic.population.Population: Add all of the specified members to this population.
addAttribute(String, String) - Method in class org.encog.parse.tags.write.WriteTags: Add an attribute to be written with the next tag.
addCDATA(String) - Method in class org.encog.parse.tags.write.WriteTags: Add CDATA to the output stream.
addColumn(int, boolean) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Add a column.
addContent(DocumentRange) - Method in class org.encog.bot.browse.WebPage: Add to the content collection.
addDataUnit(DataUnit) - Method in class org.encog.bot.browse.WebPage: Add a data unit to the collection.
addDescription(TemporalDataDescription) - Method in class org.encog.neural.data.market.MarketNeuralDataSet: Add one description of the type of market data that we are seeking at each datapoint.
addDescription(TemporalDataDescription) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Add a data description.
addElement(DocumentRange) - Method in class org.encog.bot.browse.range.DocumentRange: Add an element.
addField(OutputFieldGrouped) - Method in class org.encog.normalize.output.BasicOutputFieldGroup: Add a field to this group.
addField(OutputFieldGrouped) - Method in interface org.encog.normalize.output.OutputFieldGroup: Add an output field to the group.
addFieldMapping(int, Field, Object) - Method in class org.encog.persist.persistors.generic.ObjectMapper: Add a field mapping to be resolved later.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.ADALINEPattern: Not used, the ADALINE has no hidden layers, this will throw an error.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.ART1Pattern: This will fail, hidden layers are not supported for this type of network.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.BAMPattern: Unused, a BAM has no hidden layers.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.BoltzmannPattern: Not supported, will throw an exception, Boltzmann networks have no hidden layers.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.CPNPattern: Not used, will throw an error.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.ElmanPattern: Add a hidden layer with the specified number of neurons.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.FeedForwardPattern: Add a hidden layer, with the specified number of neurons.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.HopfieldPattern: Add a hidden layer.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.JordanPattern: Add a hidden layer, there should be only one.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.NEATPattern: Add the hidden layer, this should be called once, as a RBF has a single hidden layer.
addHiddenLayer(int) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Add the specified hidden layer.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.RadialBasisPattern: Add the hidden layer, this should be called once, as a RBF has a single hidden layer.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.RSOMPattern: Add a hidden layer.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.SOMPattern: Add a hidden layer.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.SVMPattern: Unused, a BAM has no hidden layers.
addHiddenLayer(int, int) - Method in class org.encog.neural.prune.PruneIncremental: Add a hidden layer's min and max.
addInputField(InputField) - Method in class org.encog.normalize.DataNormalization: Add an input field.
addItem(InputField, double) - Method in class org.encog.normalize.output.nominal.OutputEquilateral: Add a nominal value based on a single value.
addItem(InputField, double, double) - Method in class org.encog.normalize.output.nominal.OutputEquilateral: Add a nominal item based on a range.
addItem(InputField, double) - Method in class org.encog.normalize.output.nominal.OutputOneOf: Add a nominal value specifying a single value, the high and low values will be 0.5 below and 0.5 above.
addItem(InputField, double, double) - Method in class org.encog.normalize.output.nominal.OutputOneOf: Add a nominal item, specify the low and high values.
addLayer(Layer) - Method in class org.encog.neural.networks.BasicNetwork: Add a layer to the neural network.
addLayer(Layer, SynapseType) - Method in class org.encog.neural.networks.BasicNetwork: Add a layer to the neural network.
addLayer(Layer) - Method in interface org.encog.neural.networks.Network: Add a layer to the neural network.
addLayer(Layer, SynapseType) - Method in interface org.encog.neural.networks.Network: Add a layer to the neural network.
addNeuronID(long, List<Long>) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Add a neuron.
addNext(Layer) - Method in class org.encog.neural.networks.layers.BasicLayer: Add a layer as the next layer.
addNext(Layer, SynapseType) - Method in class org.encog.neural.networks.layers.BasicLayer
addNext(Layer) - Method in interface org.encog.neural.networks.layers.Layer: Add a layer to this layer.
addNext(Layer, SynapseType) - Method in interface org.encog.neural.networks.layers.Layer: Add a layer to this layer.
addObjectMapping(int, Object) - Method in class org.encog.persist.persistors.generic.ObjectMapper: Add an object mapping to be resolved later.
addOutputField(OutputField) - Method in class org.encog.normalize.DataNormalization: Add an output field.
addOutputField(OutputField, boolean) - Method in class org.encog.normalize.DataNormalization: Add a field and allow it to be specified as an "ideal output field".
addPattern(NeuralData, NeuralData) - Method in class org.encog.neural.networks.logic.BAMLogic: Add a pattern to the neural network.
addPattern(NeuralData) - Method in class org.encog.neural.networks.logic.HopfieldLogic: Train the neural network for the specified pattern.
addPerformer(ConcurrentTrainingPerformer) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Add a performer.
addProperty(String, double) - Method in class org.encog.parse.tags.write.WriteTags: Add a property as a double.
addProperty(String, int) - Method in class org.encog.parse.tags.write.WriteTags: Add a property as an integer.
addProperty(String, String) - Method in class org.encog.parse.tags.write.WriteTags: Add a property as a string.
addProperty(String, double[], int) - Method in class org.encog.parse.tags.write.WriteTags: Write an array as a property.
addProperty(String, int[], int) - Method in class org.encog.parse.tags.write.WriteTags: Write an array as a property.
addRange(double, double, double) - Method in class org.encog.normalize.output.mapped.OutputFieldEncode: Add a ranged mapped to a value.
addRange(double, double, boolean) - Method in class org.encog.normalize.segregate.RangeSegregator: Add a range.
addRange(SegregationRange) - Method in class org.encog.normalize.segregate.RangeSegregator: Add a range.
Address - Class in org.encog.bot.browse: A URL address.
Address(URL) - Constructor for class org.encog.bot.browse.Address: Construct the address from a URL.
Address(URL, String) - Constructor for class org.encog.bot.browse.Address: Construct a URL using a perhaps relative URL and a base URL.
addRow(int) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Add a row.
addSegregator(Segregator) - Method in class org.encog.normalize.DataNormalization: Add a segregator.
addSpeciesMember(Species, Genome) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Add a genome.
addStrategy(Strategy) - Method in class org.encog.neural.networks.training.BasicTraining: Training strategies can be added to improve the training results.
addStrategy(Strategy) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Not supported, will throw an error.
addStrategy(Strategy) - Method in interface org.encog.neural.networks.training.Train: Training strategies can be added to improve the training results.
addSubset(NeuralDataSet) - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Add a subset.
addSynapse(Synapse) - Method in class org.encog.neural.networks.layers.BasicLayer: Add a synapse to the list of outbound synapses.
addSynapse(Synapse) - Method in interface org.encog.neural.networks.layers.Layer: This method adds a synapse to the neural network.
addText(String) - Method in class org.encog.parse.tags.write.WriteTags: Add text.
addTrainingJob(TrainingJob) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Add a training job.
adjustCompatibilityThreshold() - Method in class org.encog.neural.networks.training.neat.NEATTraining: Adjust the species compatibility threshold.
adjustSpeciesScore() - Method in class org.encog.neural.networks.training.neat.NEATTraining: Adjust each species score.
adjustWeights() - Method in class org.encog.neural.networks.logic.ART1Logic: Adjust the weights for the pattern just presented.
advance(String) - Method in class org.encog.persist.PersistReader: Advance to the specified object.
advanceObjectsCollection() - Method in class org.encog.persist.PersistReader: Advance to the objects collection.
allConsoleLogging() - Static method in class org.encog.util.logging.Logging: Log everything to the console.
alreadyHaveThisNeuronID(long) - Method in class org.encog.neural.networks.training.neat.NEATGenome: Do we already have this neuron id?
analyze(EncogPersistedObject) - Method in class org.encog.persist.persistors.generic.ObjectTagger: Analyze the specified object and build a reference map.
AnalyzeNetwork - Class in org.encog.neural.networks.structure: Allows the weights and bias values of the neural network to be analyzed.
AnalyzeNetwork(BasicNetwork) - Constructor for class org.encog.neural.networks.structure.AnalyzeNetwork: Construct a network analyze class.
applyBonus(double, double) - Method in class org.encog.solve.genetic.genome.GenomeComparator: Apply a bonus, this is a simple percent that is applied in the direction specified by the "should minimize" property of the score function.
applyMinMax(double) - Method in class org.encog.normalize.input.BasicInputField: Given the current value, apply to the min and max values.
applyMinMax(double) - Method in interface org.encog.normalize.input.InputField: Update the min and max values for this field with the specified values.
applyPenalty(double, double) - Method in class org.encog.solve.genetic.genome.GenomeComparator: Apply a penalty, this is a simple percent that is applied in the direction specified by the "should minimize" property of the score function.
areCPUsPresent() - Method in class org.encog.engine.opencl.EncogCL
array2Buffer(float[], cl_mem) - Method in class org.encog.engine.opencl.EncogCLQueue: Copy a float array to a buffer.
array2Buffer(int[], cl_mem) - Method in class org.encog.engine.opencl.EncogCLQueue: Copy an int array to a buffer.
arrayCopy(double[]) - Static method in class org.encog.engine.util.EngineArray: Copy a double array.
arrayCopy(double[], double[]) - Static method in class org.encog.engine.util.EngineArray: Completely copy one array into another.
arrayCopy(double[], float[]) - Static method in class org.encog.engine.util.EngineArray: Copy an array of floats to an array of doubles.
arrayCopy(double[], int, double[], int, int) - Static method in class org.encog.engine.util.EngineArray: Copy an array of doubles.
arrayCopy(double[][]) - Static method in class org.encog.engine.util.EngineArray: Copy a 2D double array.
arrayCopy(float[], double[]) - Static method in class org.encog.engine.util.EngineArray: Copy an array of floats to an array of doubles.
arrayCopy(int[]) - Static method in class org.encog.engine.util.EngineArray: Copy an int array.
arrayCopy(int[], int[]) - Static method in class org.encog.engine.util.EngineArray: Completely copy one array into another.
ArrayDataCODEC - Class in org.encog.neural.data.buffer.codec: A CODEC used for arrays.
ArrayDataCODEC(double[][], double[][]) - Constructor for class org.encog.neural.data.buffer.codec.ArrayDataCODEC: Construct an array CODEC.
ArrayDataCODEC() - Constructor for class org.encog.neural.data.buffer.codec.ArrayDataCODEC: Default constructor.
arrayToNetwork(double[], BasicNetwork) - Static method in class org.encog.neural.networks.structure.NetworkCODEC: Use an array to populate the memory of the neural network.
ART1Logic - Class in org.encog.neural.networks.logic: Provides the neural logic for an ART1 type network.
ART1Logic() - Constructor for class org.encog.neural.networks.logic.ART1Logic
ART1Pattern - Class in org.encog.neural.pattern: Pattern to create an ART-1 neural network.
ART1Pattern() - Constructor for class org.encog.neural.pattern.ART1Pattern
ARTLogic - Class in org.encog.neural.networks.logic: Base class for all forms of the adaptive resonance theory (ART) classes.
ARTLogic() - Constructor for class org.encog.neural.networks.logic.ARTLogic
assignGeneID() - Method in class org.encog.solve.genetic.population.BasicPopulation
assignGeneID() - Method in interface org.encog.solve.genetic.population.Population
assignGenomeID() - Method in class org.encog.solve.genetic.population.BasicPopulation
assignGenomeID() - Method in interface org.encog.solve.genetic.population.Population
assignID() - Method in class org.encog.neural.networks.structure.NeuralStructure: Assign an ID to every layer that does not already have one.
assignID(Layer) - Method in class org.encog.neural.networks.structure.NeuralStructure: Assign an ID to the specified layer.
assignInnovationID() - Method in class org.encog.solve.genetic.population.BasicPopulation
assignInnovationID() - Method in interface org.encog.solve.genetic.population.Population
assignSpeciesID() - Method in class org.encog.solve.genetic.population.BasicPopulation
assignSpeciesID() - Method in interface org.encog.solve.genetic.population.Population
assignWorkgroupSizes(int, int) - Method in class org.encog.engine.opencl.kernels.KernelNetworkTrain: Assign the workgroup sizes based on the training set size.
AsynchronousCloudRequest - Class in org.encog.cloud: An asynchronous cloud request is set to the cloud, but we do not require a reply.
AsynchronousCloudRequest(URL) - Constructor for class org.encog.cloud.AsynchronousCloudRequest: Construct the cloud request.
AsynchronousCloudRequest(URL, Map<String, String>) - Constructor for class org.encog.cloud.AsynchronousCloudRequest: Construct the cloud request.
ATTRIBUTE_DESCRIPTION - Static variable in class org.encog.persist.EncogPersistedCollection: The description attribute.
ATTRIBUTE_FROM - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The from attribute.
ATTRIBUTE_ID - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The id attribute.
ATTRIBUTE_LANGUAGE - Static variable in class org.encog.persist.persistors.EncogScriptPersistor
ATTRIBUTE_LAYER - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The to attribute.
ATTRIBUTE_MATRIX_COLS - Static variable in class org.encog.persist.persistors.PersistorUtil: The columns in the matrix.
ATTRIBUTE_MATRIX_ROWS - Static variable in class org.encog.persist.persistors.PersistorUtil: The rows in the matrix.
ATTRIBUTE_NAME - Static variable in class org.encog.persist.EncogPersistedCollection: The name attribute.
ATTRIBUTE_NAME - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The name attribute.
ATTRIBUTE_NAME - Static variable in class org.encog.persist.persistors.PropertyDataPersistor: The name attribute.
ATTRIBUTE_NAME - Static variable in class org.encog.persist.persistors.TrainingContinuationPersistor: The name attribute.
ATTRIBUTE_NAME - Static variable in class org.encog.persist.PersistReader: The name attribute.
ATTRIBUTE_TO - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The to attribute.
ATTRIBUTE_TYPE - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The type attribute.
ATTRIBUTE_TYPE_BOTH - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The both layer type.
ATTRIBUTE_TYPE_HIDDEN - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The hidden layer type.
ATTRIBUTE_TYPE_INPUT - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The input layer type.
ATTRIBUTE_TYPE_OUTPUT - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The output layer type.
ATTRIBUTE_TYPE_UNKNOWN - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The unknown layer type.
ATTRIBUTE_VALUE - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The value attribute.
ATTRIBUTE_VALUE - Static variable in class org.encog.persist.persistors.PropertyDataPersistor: The value attribute.
autoDecay() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Should be called each iteration if autodecay is desired.

B

Backpropagation - Class in org.encog.neural.networks.training.propagation.back: This class implements a backpropagation training algorithm for feed forward neural networks.
Backpropagation(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.propagation.back.Backpropagation: Create a class to train using backpropagation.
Backpropagation(BasicNetwork, NeuralDataSet, double, double) - Constructor for class org.encog.neural.networks.training.propagation.back.Backpropagation: Train using the specified learning rate and momentum.
Backpropagation(BasicNetwork, NeuralDataSet, OpenCLTrainingProfile, double, double) - Constructor for class org.encog.neural.networks.training.propagation.back.Backpropagation
BAMLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for an BAM type network.
BAMLogic() - Constructor for class org.encog.neural.networks.logic.BAMLogic
BAMPattern - Class in org.encog.neural.pattern: Construct a Bidirectional Access Memory (BAM) neural network.
BAMPattern() - Constructor for class org.encog.neural.pattern.BAMPattern
BasicEngineData - Class in org.encog.engine.data: A basic implementation of the EngineData interface.
BasicEngineData(double[]) - Constructor for class org.encog.engine.data.BasicEngineData: Construct the object with only input.
BasicEngineData(double[], double[]) - Constructor for class org.encog.engine.data.BasicEngineData: Construct a BasicNeuralDataPair class with the specified input and ideal values.
BasicEngineDataSet - Class in org.encog.engine.data: Data is stored in an ArrayList.
BasicEngineDataSet() - Constructor for class org.encog.engine.data.BasicEngineDataSet: Default constructor.
BasicEngineDataSet(double[][], double[][]) - Constructor for class org.encog.engine.data.BasicEngineDataSet: Construct a data set from an input and idea array.
BasicEngineDataSet(List<EngineData>) - Constructor for class org.encog.engine.data.BasicEngineDataSet: Construct a data set from an already created list.
BasicGene - Class in org.encog.solve.genetic.genes: Implements the basic functionality for a gene.
BasicGene() - Constructor for class org.encog.solve.genetic.genes.BasicGene
BasicGenerateID - Class in org.encog.util.identity: Used to generate a unique id.
BasicGenerateID() - Constructor for class org.encog.util.identity.BasicGenerateID: Construct the ID generator to start at 1.
BasicGenome - Class in org.encog.solve.genetic.genome: A basic abstract genome.
BasicGenome(GeneticAlgorithm) - Constructor for class org.encog.solve.genetic.genome.BasicGenome: Construct a basic genome.
BasicInnovation - Class in org.encog.solve.genetic.innovation: Provides basic functionality for an innovation.
BasicInnovation() - Constructor for class org.encog.solve.genetic.innovation.BasicInnovation
BasicInnovationList - Class in org.encog.solve.genetic.innovation: Provides basic functionality for a list of innovations.
BasicInnovationList() - Constructor for class org.encog.solve.genetic.innovation.BasicInnovationList
BasicInputField - Class in org.encog.normalize.input: Provides basic functionality, such as min/max and current value for other input fields.
BasicInputField() - Constructor for class org.encog.normalize.input.BasicInputField
BasicLayer - Class in org.encog.neural.networks.layers: Basic functionality that most of the neural layers require.
BasicLayer() - Constructor for class org.encog.neural.networks.layers.BasicLayer: Default constructor, mainly so the workbench can easily create a default layer.
BasicLayer(ActivationFunction, boolean, int) - Constructor for class org.encog.neural.networks.layers.BasicLayer: Construct this layer with a non-default activation function, also determine if a bias is desired or not.
BasicLayer(int) - Constructor for class org.encog.neural.networks.layers.BasicLayer: Construct this layer with a sigmoid activation function.
BasicLayerPersistor - Class in org.encog.persist.persistors: Provides basic functions that many of the persistors will need.
BasicLayerPersistor() - Constructor for class org.encog.persist.persistors.BasicLayerPersistor
BasicMachineLearningValidate - Class in org.encog.engine.validate: Base class for validation.
BasicMachineLearningValidate() - Constructor for class org.encog.engine.validate.BasicMachineLearningValidate
BasicNetwork - Class in org.encog.neural.networks: This class implements a neural network.
BasicNetwork() - Constructor for class org.encog.neural.networks.BasicNetwork: Construct an empty neural network.
BasicNetwork(NeuralLogic) - Constructor for class org.encog.neural.networks.BasicNetwork: Construct a basic network using the specified logic.
BasicNetworkPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the BasicNetwork class.
BasicNetworkPersistor() - Constructor for class org.encog.persist.persistors.BasicNetworkPersistor
BasicNeuralData - Class in org.encog.neural.data.basic: Basic implementation of the NeuralData interface that stores the data in an array.
BasicNeuralData(double[]) - Constructor for class org.encog.neural.data.basic.BasicNeuralData: Construct this object with the specified data.
BasicNeuralData(int) - Constructor for class org.encog.neural.data.basic.BasicNeuralData: Construct this object with blank data and a specified size.
BasicNeuralData(NeuralData) - Constructor for class org.encog.neural.data.basic.BasicNeuralData: Construct a new BasicNeuralData object from an existing one.
BasicNeuralDataPair - Class in org.encog.neural.data.basic: A basic implementation of the NeuralDataPair interface.
BasicNeuralDataPair(NeuralData) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataPair: Construct the object with only input.
BasicNeuralDataPair(NeuralData, NeuralData) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataPair: Construct a BasicNeuralDataPair class with the specified input and ideal values.
BasicNeuralDataSet - Class in org.encog.neural.data.basic: neural data in an ArrayList.
BasicNeuralDataSet() - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet: Default constructor.
BasicNeuralDataSet(double[][], double[][]) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet: Construct a data set from an input and idea array.
BasicNeuralDataSet(List<NeuralDataPair>) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet: Construct a data set from an already created list.
BasicNeuralDataSet.BasicNeuralIterator - Class in org.encog.neural.data.basic: An iterator to be used with the BasicNeuralDataSet.
BasicNeuralDataSet.BasicNeuralIterator() - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet.BasicNeuralIterator
BasicNeuralDataSetPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationBiPolar class.
BasicNeuralDataSetPersistor() - Constructor for class org.encog.persist.persistors.BasicNeuralDataSetPersistor
BasicOutputField - Class in org.encog.normalize.output: Provides very basic functionality for output fields.
BasicOutputField() - Constructor for class org.encog.normalize.output.BasicOutputField
BasicOutputFieldGroup - Class in org.encog.normalize.output: Provides very basic functionality that other output field groups will use.
BasicOutputFieldGroup() - Constructor for class org.encog.normalize.output.BasicOutputFieldGroup
BasicPersistedObject - Class in org.encog.persist: A basic Encog persisted object.
BasicPersistedObject() - Constructor for class org.encog.persist.BasicPersistedObject
BasicPersistedSubObject - Class in org.encog.persist: Provides a basic implementation for an Encog persisted object that is not top level.
BasicPersistedSubObject() - Constructor for class org.encog.persist.BasicPersistedSubObject
BasicPopulation - Class in org.encog.solve.genetic.population: Defines the basic functionality for a population of genomes.
BasicPopulation() - Constructor for class org.encog.solve.genetic.population.BasicPopulation: Construct an empty population.
BasicPopulation(int) - Constructor for class org.encog.solve.genetic.population.BasicPopulation: Construct a population.
BasicRandomizer - Class in org.encog.mathutil.randomize: Provides basic functionality that most randomizers will need.
BasicRandomizer() - Constructor for class org.encog.mathutil.randomize.BasicRandomizer: Construct a random number generator with a random(current time) seed.
BasicRBF - Class in org.encog.mathutil.rbf: Basic radial basis function.
BasicRBF() - Constructor for class org.encog.mathutil.rbf.BasicRBF
BasicSpecies - Class in org.encog.solve.genetic.species: Provides basic functionality for a species.
BasicSpecies() - Constructor for class org.encog.solve.genetic.species.BasicSpecies: Default constructor, used mainly for persistence.
BasicSpecies(Population, Genome, long) - Constructor for class org.encog.solve.genetic.species.BasicSpecies: Construct a species.
BasicSynapse - Class in org.encog.neural.networks.synapse: An abstract class that implements basic functionality that may be needed by the other synapse classes.
BasicSynapse() - Constructor for class org.encog.neural.networks.synapse.BasicSynapse
BasicTraining - Class in org.encog.neural.networks.training: An abstract class that implements basic training for most training algorithms.
BasicTraining() - Constructor for class org.encog.neural.networks.training.BasicTraining
begin() - Method in class org.encog.persist.PersistWriter: Begin an Encog document.
beginDocument() - Method in class org.encog.parse.tags.write.WriteTags: Called to begin the document.
beginEncogObject(String, WriteXML, EncogPersistedObject, boolean) - Static method in class org.encog.persist.persistors.PersistorUtil: Write the beginning XML for an Encog object.
beginLoad(int, int) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Begin loading to the binary file.
beginObjects() - Method in class org.encog.persist.PersistWriter: Begin the objects collection.
beginRow() - Method in class org.encog.normalize.output.nominal.NominalItem: Begin a row.
beginScan(File) - Method in class org.encog.util.obj.GenerateClasslist: Scan a directory.
beginTag(String) - Method in class org.encog.parse.tags.write.WriteTags: Begin a tag with the specified name.
beginTask(String) - Method in class org.encog.cloud.EncogCloud: Begin a task with the specified name.
BestMatchingUnit - Class in org.encog.neural.networks.training.competitive: The "Best Matching Unit" or BMU is a very important concept in the training for a SOM.
BestMatchingUnit(CompetitiveTraining) - Constructor for class org.encog.neural.networks.training.competitive.BestMatchingUnit: Construct a BestMatchingUnit class.
bestScore(double, double) - Method in class org.encog.solve.genetic.genome.GenomeComparator: Determine the best score from two scores, uses the "should minimize" property of the score function.
binary2External(File) - Method in class org.encog.neural.data.buffer.BinaryDataLoader: Convert an Encog binary file to an external form, such as CSV.
BinaryDataLoader - Class in org.encog.neural.data.buffer: This class is used, together with a CODEC, to move data to/from the Encog binary training file format.
BinaryDataLoader(DataSetCODEC) - Constructor for class org.encog.neural.data.buffer.BinaryDataLoader: Construct a loader with the specified CODEC.
bipolar2double(boolean) - Static method in class org.encog.mathutil.matrices.BiPolarUtil: Convert a boolean to a bipolar number.
bipolar2double(boolean[]) - Static method in class org.encog.mathutil.matrices.BiPolarUtil: Convert a boolean array to a bipolar array.
bipolar2double(boolean[][]) - Static method in class org.encog.mathutil.matrices.BiPolarUtil
BiPolarNeuralData - Class in org.encog.neural.data.bipolar: A NeuralData implementation designed to work with bipolar data.
BiPolarNeuralData(boolean[]) - Constructor for class org.encog.neural.data.bipolar.BiPolarNeuralData: Construct this object with the specified data.
BiPolarNeuralData(int) - Constructor for class org.encog.neural.data.bipolar.BiPolarNeuralData: Construct a data object with the specified size.
BiPolarUtil - Class in org.encog.mathutil.matrices: This class contains a number of utility methods used to work with bipolar numbers.
BoltzmannLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for an Boltzmann type network.
BoltzmannLogic() - Constructor for class org.encog.neural.networks.logic.BoltzmannLogic
BoltzmannPattern - Class in org.encog.neural.pattern: Pattern to create a Boltzmann machine.
BoltzmannPattern() - Constructor for class org.encog.neural.pattern.BoltzmannPattern
BotError - Exception in org.encog.bot: Used to represent any error that occurs in the bot part of Encog.
BotError(String) - Constructor for exception org.encog.bot.BotError: Construct a message exception.
BotError(Throwable) - Constructor for exception org.encog.bot.BotError: Construct an exception that holds another exception.
BotUtil - Class in org.encog.bot: Utility class for bots.
bound(double) - Static method in class org.encog.engine.util.BoundNumbers: Bound the number so that it does not become too big or too small.
BoundMath - Class in org.encog.engine.util: Java will sometimes return Math.NaN or Math.Infinity when numbers get to large or too small.
BoundNumbers - Class in org.encog.engine.util: A simple class that prevents numbers from getting either too big or too small.
boxMuller(double, double) - Method in class org.encog.mathutil.randomize.GaussianRandomizer: Compute a Gaussian random number.
BPROPJob - Class in org.encog.neural.networks.training.concurrent.jobs: A training definition for BPROP training.
BPROPJob(BasicNetwork, NeuralDataSet, boolean, double, double) - Constructor for class org.encog.neural.networks.training.concurrent.jobs.BPROPJob: Construct a job definition for RPROP.
BPROPJob(BasicNetwork, NeuralDataSet, boolean, double, double, double, int, double, int) - Constructor for class org.encog.neural.networks.training.concurrent.jobs.BPROPJob: Construct a job definition for RPROP.
BrowseError - Exception in org.encog.bot.browse: Thrown when any sort of error related to web browsing is encountered.
BrowseError(String) - Constructor for exception org.encog.bot.browse.BrowseError: Construct a message exception.
BrowseError(Throwable) - Constructor for exception org.encog.bot.browse.BrowseError: Construct an exception that holds another exception.
Browser - Class in org.encog.bot.browse: The main class for web browsing.
Browser() - Constructor for class org.encog.bot.browse.Browser
buffer2Array(cl_mem, float[]) - Method in class org.encog.engine.opencl.EncogCLQueue: Copy a buffer to a float array.
buffer2Array(cl_mem, int[]) - Method in class org.encog.engine.opencl.EncogCLQueue: Copy a buffer to an int array.
BUFFER_SIZE - Static variable in class org.encog.bot.BotUtil: How much data to read at once.
BUFFER_SIZE - Static variable in class org.encog.util.file.Directory: Default buffer size for read/write operations.
BUFFER_SIZE - Static variable in class org.encog.util.http.FormUtility: The size of the read buffer.
BufferedDataError - Exception in org.encog.neural.data.buffer: An error occurs working with the Encog binary training format.
BufferedDataError(String) - Constructor for exception org.encog.neural.data.buffer.BufferedDataError: Construct a message exception.
BufferedDataError(Throwable) - Constructor for exception org.encog.neural.data.buffer.BufferedDataError: Construct an exception that holds another exception.
BufferedDataError(String, Throwable) - Constructor for exception org.encog.neural.data.buffer.BufferedDataError: Construct an exception that holds another exception.
BufferedDataSetIterator - Class in org.encog.neural.data.buffer: An iterator for the BufferedNeuralDataSet.
BufferedDataSetIterator(BufferedNeuralDataSet) - Constructor for class org.encog.neural.data.buffer.BufferedDataSetIterator: Construct the iterator.
BufferedNeuralDataSet - Class in org.encog.neural.data.buffer: This class is not memory based, so very long files can be used, without running out of memory.
BufferedNeuralDataSet(File) - Constructor for class org.encog.neural.data.buffer.BufferedNeuralDataSet: Construct the dataset using the specified binary file.
BufferedNeuralDataSetPersistor - Class in org.encog.persist.persistors
BufferedNeuralDataSetPersistor() - Constructor for class org.encog.persist.persistors.BufferedNeuralDataSetPersistor
buildDirectory() - Method in interface org.encog.persist.EncogCollection: Build the directory.
buildDirectory() - Method in class org.encog.persist.EncogMemoryCollection: Build the directory.
buildDirectory() - Method in class org.encog.persist.EncogPersistedCollection: Build a directory of objects.
buildDirectory() - Method in class org.encog.persist.PersistReader: Build a directory entry list for the file.
buildForNetworkInput(double[]) - Method in class org.encog.normalize.DataNormalization: Build "input data for a neural network" based on the input values provided.

C

C - Variable in class org.encog.mathutil.libsvm.svm_parameter
C_SVC - Static variable in class org.encog.mathutil.libsvm.svm_parameter
cache_size - Variable in class org.encog.mathutil.libsvm.svm_parameter
CalcOpenCLDevice - Class in org.encog.engine.concurrency.calc: Holds an OpenCL device to perform calculation on.
CalcOpenCLDevice(EncogCLDevice, ConcurrentCalculate) - Constructor for class org.encog.engine.concurrency.calc.CalcOpenCLDevice: Construct a device to use.
calculate(double[]) - Method in interface org.encog.engine.network.rbf.RadialBasisFunction: Calculate the RBF result for the specified value.
calculate(int, int) - Method in class org.encog.engine.opencl.kernels.KernelNetworkCalc: Calculate one iteration over the specified range.
calculate(int, int, boolean, int) - Method in class org.encog.engine.opencl.kernels.KernelNetworkTrain: Calculate one iteration over the specified range.
calculate() - Method in class org.encog.engine.util.ErrorCalculation: Returns the root mean square error for a complete training set.
calculate(double[]) - Method in class org.encog.mathutil.rbf.GaussianFunction: Calculate the result from the function.
calculate(double[]) - Method in class org.encog.mathutil.rbf.InverseMultiquadricFunction: Calculate the RBF result for the specified value.
calculate(double[]) - Method in class org.encog.mathutil.rbf.MexicanHatFunction: Calculate the result from the function.
calculate(double[]) - Method in class org.encog.mathutil.rbf.MultiquadricFunction: Calculate the RBF result for the specified value.
calculate(double[]) - Method in interface org.encog.neural.networks.training.lma.ComputeJacobian: Calculate the Jacobian.
calculate(double[]) - Method in class org.encog.neural.networks.training.lma.JacobianChainRule: Calculate the Jacobian matrix.
calculate(int) - Method in class org.encog.normalize.output.mapped.OutputFieldEncode: Calculate the value for this field.
calculate(int) - Method in class org.encog.normalize.output.multiplicative.OutputFieldMultiplicative: Calculate the value for this output field.
calculate(int) - Method in class org.encog.normalize.output.nominal.OutputEquilateral: Calculate the value for the specified subfield.
calculate(int) - Method in class org.encog.normalize.output.nominal.OutputOneOf: Calculate the value for the specified subfield.
calculate(int) - Method in interface org.encog.normalize.output.OutputField: Calculate the value for this field.
calculate(int) - Method in class org.encog.normalize.output.OutputFieldDirect: Calculate the value for this field.
calculate(double, double, double, double, double) - Static method in class org.encog.normalize.output.OutputFieldRangeMapped: Calculate a ranged mapped value.
calculate(int) - Method in class org.encog.normalize.output.OutputFieldRangeMapped: Calculate this output field.
calculate(int) - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxis: Calculate the current value for this field.
calculate(int) - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxisSynthetic: Calculate the synthetic value for this Z-Axis normalization.
calculateActualSetSize() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Calculate the actual set size, this is the number of training set entries that will be generated.
calculateARCTAN() - Method in class org.encog.engine.util.ErrorCalculation: Calculate the error with ARCTAN.
calculateBMU(Synapse, NeuralData) - Method in class org.encog.neural.networks.training.competitive.BestMatchingUnit: Calculate the best matching unit (BMU).
CalculateDepth - Class in org.encog.neural.networks.structure: Utility class to calculate the depth that a layer is from the output layer.
CalculateDepth(BasicNetwork) - Constructor for class org.encog.neural.networks.structure.CalculateDepth: Construct the depth calculation object.
calculateEnergy() - Method in class org.encog.neural.networks.logic.ThermalLogic
calculateError() - Method in class org.encog.engine.concurrency.calc.CalcOpenCLDevice: Calculate the error for the neural network using the training set.
calculateError() - Method in class org.encog.engine.concurrency.calc.ConcurrentCalculate
calculateError(EngineIndexableSet) - Method in class org.encog.engine.network.flat.FlatNetwork: Calculate the error for this neural network.
calculateError(NeuralDataSet) - Method in class org.encog.neural.networks.BasicNetwork: Calculate the error for this neural network.
calculateError(NeuralDataSet) - Method in interface org.encog.neural.networks.Network: Calculate the error for this neural network.
calculateEuclideanDistance(Synapse, NeuralData, int) - Method in class org.encog.neural.networks.training.competitive.BestMatchingUnit: Calculate the Euclidean distance for the specified output neuron and the input vector.
calculateGeneCount() - Method in class org.encog.solve.genetic.genome.BasicGenome
calculateGeneCount() - Method in interface org.encog.solve.genetic.genome.Genome
CalculateGenomeScore - Interface in org.encog.solve.genetic.genome: Genetic Algorithms need a class to calculate the score.
calculateGradients() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Calculate the gradients.
calculateGradients() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkSCG: Calculate the gradients.
calculateHessian(double[][], double[]) - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining: Calculate the Hessian matrix.
calculateKernelParams(EncogKernel, EngineIndexableSet) - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile: Calculate the kernel values.
calculateMSE() - Method in class org.encog.engine.util.ErrorCalculation: Calculate the error with MSE.
calculateNeuronCount() - Method in class org.encog.neural.networks.BasicNetwork: Calculate the total number of neurons in the network across all layers.
calculateNeuronCount() - Method in interface org.encog.neural.networks.Network: Calculate the total number of neurons in the network across all layers.
calculateNeuronCounts() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Calculate how many input and output neurons will be needed for the current data.
calculatePointsInRange() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Calculate how many points are in the high and low range.
calculateRMS() - Method in class org.encog.engine.util.ErrorCalculation: Calculate the error with RMS.
calculateScore() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Used to pass the determineError call on to the parent object.
CalculateScore - Interface in org.encog.neural.networks.training: Used by simulated annealing and genetic algorithms to calculate the score for a neural network.
calculateScore(BasicNetwork) - Method in interface org.encog.neural.networks.training.CalculateScore: Calculate this network's score.
calculateScore(Genome) - Method in class org.encog.neural.networks.training.genetic.GeneticScoreAdapter: Calculate the genome's score.
calculateScore(BasicNetwork) - Method in class org.encog.neural.networks.training.TrainingSetScore: Calculate the score for the network.
calculateScore() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Subclasses should provide a method that evaluates the score for the current solution.
calculateScore(Genome) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Calculate the score for this genome.
calculateScore(Genome) - Method in interface org.encog.solve.genetic.genome.CalculateGenomeScore: Calculate this genome's score.
calculateSize() - Method in class org.encog.neural.networks.structure.NeuralStructure: Calculate the size that an array should be to hold all of the weights and bias values.
calculateSpawnAmount() - Method in class org.encog.solve.genetic.species.BasicSpecies: Calculate the amount to spawn.
calculateSpawnAmount() - Method in interface org.encog.solve.genetic.species.Species: Calculate the amount that a species will spawn.
calculateStartIndex() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Calculate the index to start at.
calculateWorkers() - Method in class org.encog.engine.concurrency.DetermineWorkload: Calculate the high and low ranges for each worker.
CalculationResult - Class in org.encog.engine.concurrency.calc: The result from a calculation.
CalculationResult(boolean, boolean) - Constructor for class org.encog.engine.concurrency.calc.CalculationResult: Construct a calculation result.
canContinue() - Method in class org.encog.neural.networks.training.propagation.Propagation
canContinue() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
CDATA_BEGIN - Static variable in class org.encog.parse.tags.TagConst: The beginning of a CDATA section.
CDATA_END - Static variable in class org.encog.parse.tags.TagConst: THe end of a CDATA section.
changeNeuronCount(Layer, int) - Method in class org.encog.neural.prune.PruneSelective: Change the neuron count for the network.
CHAR_BULLET - Static variable in class org.encog.parse.tags.read.ReadTags: The bullet character.
CHAR_TRADEMARK - Static variable in class org.encog.parse.tags.read.ReadTags: The bullet character.
CharGene - Class in org.encog.solve.genetic.genes: A gene that holds a single character.
CharGene() - Constructor for class org.encog.solve.genetic.genes.CharGene
checkError() - Method in class org.encog.engine.concurrency.EngineConcurrency: Check to see if one of the threads has thrown an error.
checkInnovation(long, long, NEATInnovationType) - Method in class org.encog.neural.networks.training.neat.NEATInnovationList: Check to see if we already have an innovation.
CholeskyDecomposition - Class in org.encog.mathutil.matrices.decomposition: Cholesky Decomposition.
CholeskyDecomposition(Matrix) - Constructor for class org.encog.mathutil.matrices.decomposition.CholeskyDecomposition: Cholesky algorithm for symmetric and positive definite matrix.
chooseDevice() - Method in class org.encog.engine.opencl.EncogCL: Choose a device.
chooseDevice(boolean) - Method in class org.encog.engine.opencl.EncogCL: Choose a device.
chooseParent() - Method in class org.encog.solve.genetic.species.BasicSpecies: Choose a parent to mate.
chooseParent() - Method in interface org.encog.solve.genetic.species.Species: Choose a worthy parent for mating.
Chromosome - Class in org.encog.solve.genetic.genome: Implements a chromosome to genetic algorithm.
Chromosome() - Constructor for class org.encog.solve.genetic.genome.Chromosome
clear() - Method in class org.encog.mathutil.matrices.Matrix: Set all rows and columns to zero.
clear() - Method in class org.encog.neural.data.basic.BasicNeuralData: Set all data to zero.
clear() - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Set all data to false.
clear() - Method in interface org.encog.neural.data.NeuralData: Clear any data to zero.
clear() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Clear the entire dataset.
clear() - Method in class org.encog.neural.networks.logic.BAMLogic: Clear any connection weights.
clear() - Method in class org.encog.neural.networks.logic.ThermalLogic: Clear any connection weights.
clear() - Method in class org.encog.neural.pattern.ADALINEPattern: Clear out any parameters.
clear() - Method in class org.encog.neural.pattern.ART1Pattern: Clear any properties set for this network.
clear() - Method in class org.encog.neural.pattern.BAMPattern: Clear any settings on the pattern.
clear() - Method in class org.encog.neural.pattern.BoltzmannPattern: Clear any properties set on this network.
clear() - Method in class org.encog.neural.pattern.CPNPattern: Clear any parameters that were set.
clear() - Method in class org.encog.neural.pattern.ElmanPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.neural.pattern.FeedForwardPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.neural.pattern.HopfieldPattern: Nothing to clear.
clear() - Method in class org.encog.neural.pattern.JordanPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.neural.pattern.NEATPattern: Clear out any hidden neurons.
clear() - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Clear the hidden layers so that they can be redefined.
clear() - Method in class org.encog.neural.pattern.RadialBasisPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.neural.pattern.RSOMPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.neural.pattern.SOMPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.neural.pattern.SVMPattern: Clear any settings on the pattern.
clear() - Method in class org.encog.parse.tags.Tag: Clear the name, type and attributes.
clear() - Method in interface org.encog.persist.EncogCollection: Clear all elements from the collection.
clear() - Method in class org.encog.persist.EncogMemoryCollection: Clear all elements from the collection.
clear() - Method in class org.encog.persist.EncogPersistedCollection: Clear the collection.
clear() - Method in class org.encog.persist.persistors.generic.ObjectMapper: Clear the map and reference list.
clear() - Method in class org.encog.persist.persistors.generic.ObjectTagger: Clear the map and current id.
clear() - Method in class org.encog.solve.genetic.population.BasicPopulation: Clear all genomes from this population.
clear() - Method in interface org.encog.solve.genetic.population.Population: Clear all genomes from this population.
clearConnectionLimit() - Method in class org.encog.engine.network.flat.FlatNetwork
clearContext() - Method in class org.encog.engine.network.flat.FlatNetwork: Clear any context neurons.
clearContext() - Method in class org.encog.neural.networks.BasicNetwork: Clear any data from any context layers.
clearContext() - Method in interface org.encog.neural.networks.ContextClearable: Clear the context for this layer.
clearContext() - Method in class org.encog.neural.networks.layers.ContextLayer: Reset the context values back to zero.
clearContext() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Clear any context from previous runs.
clearLayerTags() - Method in class org.encog.neural.networks.BasicNetwork: Remove all layer tags.
clearPerformers() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Clear all of the performers.
clearQueue() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Clear the workload.
clone() - Method in class org.encog.engine.network.activation.ActivationBiPolar
clone() - Method in class org.encog.engine.network.activation.ActivationCompetitive
clone() - Method in interface org.encog.engine.network.activation.ActivationFunction
clone() - Method in class org.encog.engine.network.activation.ActivationGaussian
clone() - Method in class org.encog.engine.network.activation.ActivationLinear
clone() - Method in class org.encog.engine.network.activation.ActivationLOG
clone() - Method in class org.encog.engine.network.activation.ActivationRamp: Clone the object.
clone() - Method in class org.encog.engine.network.activation.ActivationSigmoid
clone() - Method in class org.encog.engine.network.activation.ActivationSIN
clone() - Method in class org.encog.engine.network.activation.ActivationSoftMax
clone() - Method in class org.encog.engine.network.activation.ActivationStep
clone() - Method in class org.encog.engine.network.activation.ActivationTANH
clone() - Method in class org.encog.engine.network.flat.FlatNetwork: Clone the network.
clone() - Method in class org.encog.engine.network.flat.FlatNetworkRBF: Clone the network.
clone() - Method in class org.encog.mathutil.libsvm.svm_parameter
clone() - Method in class org.encog.mathutil.matrices.Matrix: Create a copy of the matrix.
clone() - Method in class org.encog.neural.data.basic.BasicNeuralData
clone() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
clone() - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData
clone() - Method in interface org.encog.neural.data.NeuralData: Clone this object.
clone() - Method in class org.encog.neural.data.PropertyData: Clone this object.
clone() - Method in class org.encog.neural.data.TextData: Clone this object.
clone() - Method in class org.encog.neural.networks.BasicNetwork: Return a clone of this neural network.
clone() - Method in interface org.encog.neural.networks.Network: Return a clone of this neural network.
clone() - Method in class org.encog.neural.networks.synapse.BasicSynapse
clone() - Method in class org.encog.neural.networks.synapse.DirectSynapse
clone() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
clone() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
clone() - Method in interface org.encog.neural.networks.synapse.Synapse
clone() - Method in class org.encog.neural.networks.synapse.WeightedSynapse
clone() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse
clone() - Method in class org.encog.parse.tags.Tag
cloneFlatNetwork(FlatNetwork) - Method in class org.encog.engine.network.flat.FlatNetwork
close() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Close this data set.
close() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Close the dataset.
close() - Method in class org.encog.neural.data.buffer.codec.ArrayDataCODEC: Close any open files.
close() - Method in class org.encog.neural.data.buffer.codec.CSVDataCODEC: Close any open files.
close() - Method in interface org.encog.neural.data.buffer.codec.DataSetCODEC: Close any open files.
close() - Method in class org.encog.neural.data.buffer.codec.ExcelCODEC: Close any open files.
close() - Method in class org.encog.neural.data.buffer.codec.NeuralDataSetCODEC: Close any open files.
close() - Method in class org.encog.neural.data.buffer.EncogEGBFile: Close the file.
close() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet: Close any iterators from this dataset.
close() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet.CSVNeuralIterator: Close the iterator, and the underlying CSV file.
close() - Method in class org.encog.neural.data.folded.FoldedDataSet: Close the dataset.
close() - Method in interface org.encog.neural.data.NeuralDataSet: Close this datasource and release any resources obtained by it, including any iterators created.
close() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Close the SQL connection.
close() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet.SQLNeuralIterator: Close this iterator and release any resources it had.
close() - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Close the dataset.
close() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet: Close the XML data source.
close() - Method in interface org.encog.normalize.target.NormalizationStorage: Open the storage.
close() - Method in class org.encog.normalize.target.NormalizationStorageArray1D: Not needed for this storage type.
close() - Method in class org.encog.normalize.target.NormalizationStorageArray2D: Not needed for this storage type.
close() - Method in class org.encog.normalize.target.NormalizationStorageCSV: Close the CSV file.
close() - Method in class org.encog.normalize.target.NormalizationStorageEncogCollection
close() - Method in class org.encog.normalize.target.NormalizationStorageNeuralDataSet: Not needed for this storage type.
close() - Method in class org.encog.parse.tags.write.WriteTags: Close this object.
close() - Method in class org.encog.persist.PersistReader: Close the file.
close() - Method in class org.encog.persist.PersistWriter: Close the writer.
close() - Method in class org.encog.util.csv.ReadCSV: Close the file.
CloudRequest - Class in org.encog.cloud: An Encog cloud request.
CloudRequest() - Constructor for class org.encog.cloud.CloudRequest
CloudTask - Class in org.encog.cloud: Encapsulates an Encog cloud task.
CloudTask(EncogCloud) - Constructor for class org.encog.cloud.CloudTask: Construct a cloud task.
code(TimeUnit) - Method in class org.encog.util.time.EnglishTimeUnitNames: Get the code for a TimeUnit.
code(TimeUnit) - Method in interface org.encog.util.time.TimeUnitNames: Get the code for the specified time unit.
CodeDataUnit - Class in org.encog.bot.dataunit: A data unit that holds code.
CodeDataUnit() - Constructor for class org.encog.bot.dataunit.CodeDataUnit
coef0 - Variable in class org.encog.mathutil.libsvm.svm_parameter
COMMENT_BEGIN - Static variable in class org.encog.parse.tags.TagConst: The beginning of a comment.
COMMENT_END - Static variable in class org.encog.parse.tags.TagConst: The end of a comment.
compare(Layer, Layer) - Method in class org.encog.neural.networks.structure.LayerComparator: Compare two layers.
compare(Synapse, Synapse) - Method in class org.encog.neural.networks.structure.SynapseComparator: Compare two layers.
compare(Genome, Genome) - Method in class org.encog.solve.genetic.genome.GenomeComparator: Compare two genomes.
compareTo(LoadedMarketData) - Method in class org.encog.neural.data.market.loader.LoadedMarketData
compareTo(TemporalPoint) - Method in class org.encog.neural.data.temporal.TemporalPoint
compareTo(Layer) - Method in class org.encog.neural.networks.layers.BasicLayer
compareTo(DirectoryEntry) - Method in class org.encog.persist.DirectoryEntry
compareTo(Gene) - Method in class org.encog.solve.genetic.genes.BasicGene
compareTo(Genome) - Method in class org.encog.solve.genetic.genome.BasicGenome
CompetitiveTraining - Class in org.encog.neural.networks.training.competitive: This class implements competitive training, which would be used in a winner-take-all neural network, such as the self organizing map (SOM).
CompetitiveTraining(BasicNetwork, double, NeuralDataSet, NeighborhoodFunction) - Constructor for class org.encog.neural.networks.training.competitive.CompetitiveTraining: Create an instance of competitive training.
compile() - Method in class org.encog.engine.opencl.kernels.EncogKernel: Compile the kernel with no preprocessor defines.
compile(Map<String, String>) - Method in class org.encog.engine.opencl.kernels.EncogKernel: Compile the kernel with a map of preprocessor defines, a collection of name-value pairs.
compile(FlatNetwork) - Method in class org.encog.engine.opencl.kernels.KernelNetworkCalc: Compile the kernel.
compile(Map<String, String>, OpenCLTrainingProfile, FlatNetwork) - Method in class org.encog.engine.opencl.kernels.KernelNetworkTrain: Compile the kernel.
complete() - Method in class org.encog.util.http.FormUtility: Complete the building of the form.
compute(double[], double[]) - Method in interface org.encog.engine.EngineMachineLearning: Compute output for the given input.
compute(double[], double[]) - Method in class org.encog.engine.network.flat.FlatNetwork: Calculate the output for the given input.
compute(double[], double[]) - Method in class org.encog.engine.network.flat.FlatNetworkRBF: Calculate the output for the given input.
compute(double[], double[]) - Method in class org.encog.neural.networks.BasicNetwork: Compute output for the given input.
compute(NeuralData) - Method in class org.encog.neural.networks.BasicNetwork: Compute the output for a given input to the neural network.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.BasicNetwork: Compute the output for a given input to the neural network.
compute(NeuralData) - Method in class org.encog.neural.networks.layers.BasicLayer: Compute the outputs for this layer given the input pattern.
compute(NeuralData) - Method in interface org.encog.neural.networks.layers.Layer: Compute the output for this layer.
compute(NeuralData) - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Compute the values before sending output to the next layer.
compute(BiPolarNeuralData, BiPolarNeuralData) - Method in class org.encog.neural.networks.logic.ART1Logic: Compute the output from the ART1 network.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.logic.ART1Logic: Compute the output for the BasicNetwork class.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.logic.BAMLogic: Setup the network logic, read parameters from the network.
compute(NeuralDataMapping) - Method in class org.encog.neural.networks.logic.BAMLogic: Compute the network for the specified input.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Setup the network logic, read parameters from the network.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.logic.FeedforwardLogic: Compute the output for a given input to the neural network.
compute(NeuralData, NeuralOutputHolder) - Method in interface org.encog.neural.networks.logic.NeuralLogic: Compute the output for the BasicNetwork class.
compute(NeuralData) - Method in interface org.encog.neural.networks.Network: Compute the output for a given input to the neural network.
compute(NeuralData, NeuralOutputHolder) - Method in interface org.encog.neural.networks.Network: Compute the output for a given input to the neural network.
compute(NeuralData) - Method in class org.encog.neural.networks.svm.SVMNetwork: Compute the output for the given input.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.svm.SVMNetwork: Compute the output for the given input.
compute(NeuralData) - Method in class org.encog.neural.networks.synapse.DirectSynapse: Compute the output from this synapse.
compute(NeuralData) - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Compute the output from this synapse.
compute(NeuralData) - Method in class org.encog.neural.networks.synapse.OneToOneSynapse: Compute the output from this synapse.
compute(NeuralData) - Method in interface org.encog.neural.networks.synapse.Synapse: Compute the output from this synapse.
compute(NeuralData) - Method in class org.encog.neural.networks.synapse.WeightedSynapse: Compute the weighted output from this synapse.
compute(NeuralData) - Method in class org.encog.neural.networks.synapse.WeightlessSynapse: Compute the weightless output from this synapse.
ComputeJacobian - Interface in org.encog.neural.networks.training.lma: Calculate the Jacobian.
computeLayer(int) - Method in class org.encog.engine.network.flat.FlatNetwork: Calculate a layer.
ConcurrentCalculate - Class in org.encog.engine.concurrency.calc: Class used to provide concurrent calculation between the CPU and OpenCL devices.
ConcurrentJob - Class in org.encog.engine.concurrency.job: This class forms the basis for a job that can be run concurrently.
ConcurrentJob(StatusReportable) - Constructor for class org.encog.engine.concurrency.job.ConcurrentJob: Construct a concurrent job.
ConcurrentTrainingManager - Class in org.encog.neural.networks.training.concurrent: Concurrent training manager.
ConcurrentTrainingPerformer - Interface in org.encog.neural.networks.training.concurrent.performers: Performers actually perform the training.
ConcurrentTrainingPerformerCPU - Class in org.encog.neural.networks.training.concurrent.performers: This performer allows jobs to be performed by the CPU.
ConcurrentTrainingPerformerCPU(int) - Constructor for class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
ConcurrentTrainingPerformerOpenCL - Class in org.encog.neural.networks.training.concurrent.performers: This performer allows jobs to be performed by the CPU.
ConcurrentTrainingPerformerOpenCL(int, EncogCLDevice) - Constructor for class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerOpenCL: Construct an OpenCL device performer.
cond() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition: Two norm condition number
connect(String, String) - Method in class org.encog.cloud.EncogCloud: Connect to the Encog cloud.
ConsistentRandomizer - Class in org.encog.mathutil.randomize: A randomizer that takes a seed and will always produce consistent results.
ConsistentRandomizer(double, double) - Constructor for class org.encog.mathutil.randomize.ConsistentRandomizer: Construct a range randomizer.
ConsistentRandomizer(double, double, int) - Constructor for class org.encog.mathutil.randomize.ConsistentRandomizer: Construct a range randomizer.
ConsoleInputOutput - Interface in org.encog.script
ConsoleStatusReportable - Class in org.encog: A simple status report that goes to the console.
ConsoleStatusReportable() - Constructor for class org.encog.ConsoleStatusReportable
ConstRandomizer - Class in org.encog.mathutil.randomize: A randomizer that will create always set the random number to a const value, used mainly for testing.
ConstRandomizer(double) - Constructor for class org.encog.mathutil.randomize.ConstRandomizer: Construct a range randomizer.
constructService(String) - Method in class org.encog.cloud.EncogCloud: Construct a string that connects to the specified service.
constructURL(URL, String, boolean) - Static method in class org.encog.util.http.URLUtility: Construct a URL from its basic parts.
containsInvalidURLCharacters(String) - Static method in class org.encog.util.http.URLUtility: Returns true if the URL contains any invalid characters.
containsLayerType(Class<?>) - Method in class org.encog.neural.networks.structure.NeuralStructure: Determine if the network contains a layer of the specified type.
ContextClearable - Interface in org.encog.neural.networks: Allows the clearContext method to be called.
ContextLayer - Class in org.encog.neural.networks.layers: Implements a context layer.
ContextLayer() - Constructor for class org.encog.neural.networks.layers.ContextLayer: Default constructor, mainly so the workbench can easily create a default layer.
ContextLayer(ActivationFunction, int) - Constructor for class org.encog.neural.networks.layers.ContextLayer: Construct a context layer with the parameters specified.
ContextLayer(int) - Constructor for class org.encog.neural.networks.layers.ContextLayer: Construct a default context layer that has the TANH activation function and the specified number of neurons.
ContextLayerPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ContextLayer class.
ContextLayerPersistor() - Constructor for class org.encog.persist.persistors.ContextLayerPersistor
Convert - Class in org.encog.mathutil: This class is used to convert strings into numeric values.
convertBack(double) - Method in class org.encog.normalize.output.OutputFieldRangeMapped: Convert a number back after its been normalized.
convertCSV2Binary(File, File, int, int, boolean) - Static method in class org.encog.util.simple.EncogUtility: Convert a CSV file to a binary training file.
convertFilename(String, URL, boolean) - Static method in class org.encog.util.http.URLUtility: Convert a filename for local storage.
CookieUtility - Class in org.encog.util.http: This class allows URLConnection objects to process cookies.
CookieUtility() - Constructor for class org.encog.util.http.CookieUtility
copy(Matrix, Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath: Copy from one matrix to another.
copy(NeuralDataMapping, NeuralDataMapping) - Static method in class org.encog.neural.networks.NeuralDataMapping: Copy from one object to the other.
copy(Gene) - Method in class org.encog.neural.networks.training.neat.NEATLinkGene: Copy from another gene.
copy(Gene) - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene: Copy another gene to this one.
copy(Gene) - Method in class org.encog.solve.genetic.genes.CharGene: Copy another gene to this gene.
copy(Gene) - Method in class org.encog.solve.genetic.genes.DoubleGene: Copy another gene to this one.
copy(Gene) - Method in interface org.encog.solve.genetic.genes.Gene: Copy another gene to this one.
copy(Gene) - Method in class org.encog.solve.genetic.genes.IntegerGene: Copy another gene to this one.
copyFile(File, File) - Static method in class org.encog.util.file.Directory: Copy the specified file.
copyFromNetwork(FlatNetwork) - Method in class org.encog.neural.networks.training.cross.NetworkFold: Copy the weights and output from the network.
copyToNetwork(FlatNetwork) - Method in class org.encog.neural.networks.training.cross.NetworkFold: Copy weights and output to the network.
cos(double) - Static method in class org.encog.engine.util.BoundMath: Calculate the cos.
CPNPattern - Class in org.encog.neural.pattern: Pattern that creates a CPN neural network.
CPNPattern() - Constructor for class org.encog.neural.pattern.CPNPattern
create(int, int) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Create a new RGB file.
create() - Method in class org.encog.persist.EncogPersistedCollection: Create the file.
create(EncogMemoryCollection) - Method in interface org.encog.script.IndividualEngineFactory
create() - Method in interface org.encog.script.IndividualEngineFactory
createArrayReadOnly(float[]) - Method in class org.encog.engine.opencl.kernels.EncogKernel: Create an array buffer that is read only for floats.
createArrayReadOnly(int[]) - Method in class org.encog.engine.opencl.kernels.EncogKernel: Create an array buffer that is read only for ints.
createColumnMatrix(double[]) - Static method in class org.encog.mathutil.matrices.Matrix: Turn an array of doubles into a column matrix.
createDate(int, int, int) - Static method in class org.encog.util.time.DateUtil: Create a Date object with the specified date.
createEngine(EncogScript) - Method in class org.encog.script.EncogScriptEngineFactory
createFloatArrayWriteOnly(int) - Method in class org.encog.engine.opencl.kernels.EncogKernel: Create an array buffer that is write only.
createInputStream(String) - Static method in class org.encog.engine.util.ResourceLoader: Create an input stream to read from the resource.
createInputStream() - Method in class org.encog.persist.location.FilePersistence
createInputStream() - Method in class org.encog.persist.location.InputStreamPersistence: Create the input stream.
createInputStream() - Method in class org.encog.persist.location.OutputStreamPersistence: Can't create an InputStream for this object type, throw an error.
createInputStream() - Method in interface org.encog.persist.location.PersistenceLocation
createInputStream() - Method in class org.encog.persist.location.ResourcePersistence: Create an input stream to read from the resource.
createNeuronFromID(long) - Method in class org.encog.neural.networks.training.neat.NEATInnovationList: Create a new neuron gene from an id.
createNewInnovation(long, long, NEATInnovationType) - Method in class org.encog.neural.networks.training.neat.NEATInnovationList: Create a new innovation.
createNewInnovation(long, long, NEATInnovationType, NEATNeuronType, double, double) - Method in class org.encog.neural.networks.training.neat.NEATInnovationList: Create a new innovation.
createOutputStream() - Method in class org.encog.persist.location.FilePersistence
createOutputStream() - Method in class org.encog.persist.location.InputStreamPersistence: Try to create an output stream.
createOutputStream() - Method in class org.encog.persist.location.OutputStreamPersistence: Provide the output stream to use.
createOutputStream() - Method in interface org.encog.persist.location.PersistenceLocation
createOutputStream() - Method in class org.encog.persist.location.ResourcePersistence: Write operations are not supported for resource persistence.
createPair(int, int) - Static method in class org.encog.engine.data.BasicEngineData: Create a new neural data pair object of the correct size for the neural network that is being trained.
createPair(int, int) - Static method in class org.encog.neural.data.basic.BasicNeuralDataPair: Create a new neural data pair object of the correct size for the neural network that is being trained.
createPersistor() - Method in class org.encog.mathutil.matrices.Matrix: Create a Persistor for this object.
createPersistor() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Create a persistor for this object.
createPersistor() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
createPersistor() - Method in class org.encog.neural.data.PropertyData
createPersistor() - Method in class org.encog.neural.data.TextData: Create a persistor to store this object.
createPersistor() - Method in class org.encog.neural.networks.BasicNetwork: Create a persistor for this object.
createPersistor() - Method in class org.encog.neural.networks.layers.BasicLayer: Create a persistor for this layer.
createPersistor() - Method in class org.encog.neural.networks.layers.ContextLayer: Create a persistor for this layer.
createPersistor() - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer
createPersistor() - Method in interface org.encog.neural.networks.Network: Create a persistor for this object.
createPersistor() - Method in class org.encog.neural.networks.svm.SVMNetwork: Create a persistor for this object.
createPersistor() - Method in class org.encog.neural.networks.synapse.DirectSynapse: Create a persistor for this type of synapse.
createPersistor() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
createPersistor() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
createPersistor() - Method in class org.encog.neural.networks.synapse.WeightedSynapse: Return a persistor for this object.
createPersistor() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse: Return a persistor for this object.
createPersistor() - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
createPersistor() - Method in class org.encog.persist.BasicPersistedObject: Create a persistor for this object.
createPersistor() - Method in interface org.encog.persist.EncogPersistedObject: Create a persistor for this object.
createPersistor(String) - Static method in class org.encog.persist.persistors.PersistorUtil: Create a persistor object.
createPersistor() - Method in class org.encog.script.EncogScript
createPersistor() - Method in class org.encog.solve.genetic.population.BasicPopulation
createPoint(Date) - Method in class org.encog.neural.data.market.MarketNeuralDataSet: Create a datapoint at the specified date.
createPoint(Date) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Create a temporal point from a time.
createPoint(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Create a temporal data point using a sequence number.
createRowMatrix(double[]) - Static method in class org.encog.mathutil.matrices.Matrix: Turn an array of doubles into a row matrix.
createTaskGroup() - Method in class org.encog.engine.concurrency.EngineConcurrency: Create a new task group.
createTrainer(OpenCLTrainingProfile, boolean) - Method in class org.encog.neural.networks.training.concurrent.jobs.BPROPJob: Create a trainer to use.
createTrainer(OpenCLTrainingProfile, boolean) - Method in class org.encog.neural.networks.training.concurrent.jobs.RPROPJob: Create a trainer to use.
createTrainer(OpenCLTrainingProfile, boolean) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob: Create a trainer to use.
crossover(NEATGenome, NEATGenome) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Perform the crossover.
Crossover - Interface in org.encog.solve.genetic.crossover: Specifies how "crossover" or mating happens.
CrossTraining - Class in org.encog.neural.networks.training.cross: Base class for cross training trainers.
CrossTraining(BasicNetwork, FoldedDataSet) - Constructor for class org.encog.neural.networks.training.cross.CrossTraining: Construct a cross trainer.
crossValidate(int, double, double) - Method in class org.encog.neural.networks.training.svm.SVMTrain: Cross validate and check the specified index/gamma.
CrossValidationKFold - Class in org.encog.neural.networks.training.cross: Train using K-Fold cross validation.
CrossValidationKFold(Train, int) - Constructor for class org.encog.neural.networks.training.cross.CrossValidationKFold: Construct a cross validation trainer.
CSVDataCODEC - Class in org.encog.neural.data.buffer.codec: A CODEC used to read/write data from/to a CSV data file.
CSVDataCODEC(File, CSVFormat, boolean, int, int) - Constructor for class org.encog.neural.data.buffer.codec.CSVDataCODEC: Create a CODEC to load data from CSV to binary.
CSVDataCODEC(File, CSVFormat) - Constructor for class org.encog.neural.data.buffer.codec.CSVDataCODEC: Constructor to create CSV from binary..
CSVError - Exception in org.encog.util.csv: An error has occured while working with CSV data.
CSVError(String) - Constructor for exception org.encog.util.csv.CSVError: Construct a message exception.
CSVError(Throwable) - Constructor for exception org.encog.util.csv.CSVError: Construct an exception that holds another exception.
CSVFormat - Class in org.encog.util.csv: Specifies a CSV format.
CSVFormat() - Constructor for class org.encog.util.csv.CSVFormat: By default use USA conventions.
CSVFormat(char, char) - Constructor for class org.encog.util.csv.CSVFormat: Construct a CSV format with he specified decimal and separator characters.
CSVNeuralDataSet - Class in org.encog.neural.data.csv: An implementation of the NeuralDataSet interface designed to provide a CSV file to the neural network.
CSVNeuralDataSet(String, int, int, boolean) - Constructor for class org.encog.neural.data.csv.CSVNeuralDataSet: Construct this data set using a comma as a delimiter.
CSVNeuralDataSet(String, int, int, boolean, CSVFormat) - Constructor for class org.encog.neural.data.csv.CSVNeuralDataSet: Construct this data set using a comma as a delimiter.
CSVNeuralDataSet.CSVNeuralIterator - Class in org.encog.neural.data.csv: An iterator designed to read from CSV files.
CSVNeuralDataSet.CSVNeuralIterator() - Constructor for class org.encog.neural.data.csv.CSVNeuralDataSet.CSVNeuralIterator: Default constructor.
currentError - Variable in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: The current error is the average error over all of the threads.
CUT - Static variable in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: The cutoff for random data.

D

DataNormalization - Class in org.encog.normalize: This class is used to normalize both input and ideal data for neural networks.
DataNormalization() - Constructor for class org.encog.normalize.DataNormalization
DataSetCODEC - Interface in org.encog.neural.data.buffer.codec: A CODEC is used to encode and decode data.
DataUnit - Class in org.encog.bot.dataunit: Data units are very abstract pieces of data that the browser processes.
DataUnit() - Constructor for class org.encog.bot.dataunit.DataUnit
DateUtil - Class in org.encog.util.time: Simple date utility class.
DAYS_WEEK - Static variable in class org.encog.util.time.TimeSpan: Days in a week.
decay(double) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Called to decay the learning rate and radius by the specified amount.
decay(double, double) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Decay the learning rate and radius by the specified amount.
DECIMAL_COMMA - Static variable in class org.encog.util.csv.CSVFormat: Use a decimal comma, and a semicolon to separate numbers.
DECIMAL_POINT - Static variable in class org.encog.util.csv.CSVFormat: Use a decimal point, and a comma to separate numbers.
decode(double[]) - Method in class org.encog.mathutil.Equilateral: Decode a set of activations and see which set it has the lowest Euclidean distance from.
decode() - Method in class org.encog.neural.networks.training.genetic.NeuralGenome: Decode the genomes into a neural network.
decode() - Method in class org.encog.neural.networks.training.neat.NEATGenome: Convert the genes to an actual network.
decode() - Method in interface org.encog.solve.genetic.genome.Genome: Use the genes to update the organism.
decodeNetwork(double[]) - Method in interface org.encog.engine.EngineNeuralNetwork: Decode an array to the neural network weights.
decodeNetwork(double[]) - Method in class org.encog.engine.network.flat.FlatNetwork: Decode the specified data into the weights of the neural network.
decreaseTemperature(double) - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Decrease the temperature by the specified amount.
deepCopy(Object) - Static method in class org.encog.util.obj.ObjectCloner: Perform a deep copy.
DEFAULT_ALTERNATE_CYCLES - Static variable in class org.encog.neural.networks.training.strategy.HybridStrategy: The default number of cycles to use the alternate training for.
DEFAULT_BIAS_ACTIVATION - Static variable in class org.encog.engine.network.flat.FlatNetwork: The default bias activation.
DEFAULT_CONNECTION_LIMIT - Static variable in class org.encog.neural.networks.BasicNetwork
DEFAULT_CONST_BEGIN - Static variable in class org.encog.neural.networks.training.svm.SVMTrain: The default starting number for C.
DEFAULT_CONST_END - Static variable in class org.encog.neural.networks.training.svm.SVMTrain: The default ending number for C.
DEFAULT_CONST_STEP - Static variable in class org.encog.neural.networks.training.svm.SVMTrain: The default step for C.
DEFAULT_DOUBLE_EQUAL - Static variable in class org.encog.Encog: Default point at which two doubles are equal.
DEFAULT_GAMMA_BEGIN - Static variable in class org.encog.neural.networks.training.svm.SVMTrain: The default gamma begin.
DEFAULT_GAMMA_END - Static variable in class org.encog.neural.networks.training.svm.SVMTrain: The default gamma end.
DEFAULT_GAMMA_STEP - Static variable in class org.encog.neural.networks.training.svm.SVMTrain: The default gamma step.
DEFAULT_INITIAL_UPDATE - Static variable in class org.encog.engine.network.train.prop.RPROPConst: The starting update for a delta.
DEFAULT_MAX_STEP - Static variable in class org.encog.engine.network.train.prop.RPROPConst: The maximum amount a delta can reach.
DEFAULT_MIN_IMPROVEMENT - Static variable in class org.encog.neural.networks.training.strategy.HybridStrategy: The default minimum improvement before we switch to the alternate training method.
DEFAULT_MIN_IMPROVEMENT - Static variable in class org.encog.neural.networks.training.strategy.StopTrainingStrategy: The default minimum improvement before training stops.
DEFAULT_PRECISION - Static variable in class org.encog.Encog: The default precision to use for compares.
DEFAULT_SERVER - Static variable in class org.encog.cloud.EncogCloud: The default cloud server.
DEFAULT_TOLERATE_CYCLES - Static variable in class org.encog.neural.networks.training.strategy.HybridStrategy: The default number of cycles to tolerate bad improvement for.
DEFAULT_TOLERATE_CYCLES - Static variable in class org.encog.neural.networks.training.strategy.StopTrainingStrategy: The default number of cycles to tolerate.
DEFAULT_ZERO_TOLERANCE - Static variable in class org.encog.engine.EncogEngine: The default zero tolerance.
DEFAULT_ZERO_TOLERANCE - Static variable in class org.encog.engine.network.train.prop.RPROPConst: The default zero tolerance.
deg2rad(double) - Static method in class org.encog.mathutil.EncogMath: Convert degrees to radians.
DEG_CIRCLE - Static variable in class org.encog.mathutil.MathConst: Degrees in a circle.
DEG_SEMICIRCLE - Static variable in class org.encog.mathutil.MathConst: Degrees in a semicircle.
degree - Variable in class org.encog.mathutil.libsvm.svm_parameter
delete(DirectoryEntry) - Method in interface org.encog.persist.EncogCollection: Delete an object from the collection.
delete(String) - Method in interface org.encog.persist.EncogCollection: Delete a key from the collection.
delete(DirectoryEntry) - Method in class org.encog.persist.EncogMemoryCollection: Delete an object from the collection.
delete(String) - Method in class org.encog.persist.EncogMemoryCollection: Delete a key from the collection.
delete(DirectoryEntry) - Method in class org.encog.persist.EncogPersistedCollection: Delete the specified object, use a directory entry.
delete(EncogPersistedObject) - Method in class org.encog.persist.EncogPersistedCollection: Delete the specified object.
delete(String) - Method in class org.encog.persist.EncogPersistedCollection: Delete the specified object.
delete() - Method in class org.encog.persist.location.FilePersistence: Attempt to delete the file.
delete() - Method in class org.encog.persist.location.InputStreamPersistence: Delete operations are not supported for resource persistence.
delete() - Method in class org.encog.persist.location.OutputStreamPersistence: Delete operations are not supported for resource persistence.
delete() - Method in interface org.encog.persist.location.PersistenceLocation: Delete the location, if possible.
delete() - Method in class org.encog.persist.location.ResourcePersistence: Delete operations are not supported for resource persistence.
deleteCol(Matrix, int) - Static method in class org.encog.mathutil.matrices.MatrixMath: Delete one column from the matrix.
deleteCol(int) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Delete a column.
deleteDirectory(File) - Static method in class org.encog.util.file.Directory: Delete a directory and all children.
deleteRow(Matrix, int) - Static method in class org.encog.mathutil.matrices.MatrixMath: Delete a row from the matrix.
deleteRow(int) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Delete a row.
DELTA_MIN - Static variable in class org.encog.engine.network.train.prop.RPROPConst: The minimum delta value for a weight matrix value.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationBiPolar: Implements the activation function derivative.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationCompetitive: Implements the activation function.
derivativeFunction(double) - Method in interface org.encog.engine.network.activation.ActivationFunction: Calculate the derivative of the activation.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationGaussian: Calculate the derivative of the activation.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationLinear: Calculate the derivative of the activation.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationLOG: Calculate the derivative of the activation.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationRamp: Calculate the derivative of the activation.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationSigmoid: Calculate the derivative of the activation.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationSIN: Calculate the derivative of the activation.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationSoftMax: Calculate the derivative of the activation.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationStep: Calculate the derivative of the activation.
derivativeFunction(double) - Method in class org.encog.engine.network.activation.ActivationTANH: Calculate the derivative of the activation.
det() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition: Determinant
detectPerformers() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Detect performers.
detectPerformers(boolean, int) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Detect performers.
determineNeuronSignificance(Layer, int) - Method in class org.encog.neural.prune.PruneSelective: Determine the significance of the neuron.
determineWinner(NeuralData) - Static method in class org.encog.neural.networks.BasicNetwork: Determine which member of the output is the winning neuron.
DetermineWorkload - Class in org.encog.engine.concurrency: Used by several Encog training methods to break up a workload.
DetermineWorkload(int, int) - Constructor for class org.encog.engine.concurrency.DetermineWorkload: Determine the workload.
Directory - Class in org.encog.util.file: Directory utilities.
DirectoryEntry - Class in org.encog.persist: The idea of the Encog persisted collection is that the entire file might be quite long and should not be read into memory in its entirity.
DirectoryEntry(EncogPersistedObject) - Constructor for class org.encog.persist.DirectoryEntry: Construct a directory entry for the specified object.
DirectoryEntry(String, String, String) - Constructor for class org.encog.persist.DirectoryEntry: Construct a directory entry from strings.
DirectSynapse - Class in org.encog.neural.networks.synapse: A direct synapse will present the entire input array to each of the directly connected neurons in the next layer.
DirectSynapse() - Constructor for class org.encog.neural.networks.synapse.DirectSynapse: Simple default constructor.
DirectSynapse(Layer, Layer) - Constructor for class org.encog.neural.networks.synapse.DirectSynapse: Construct a direct synapse between the two specified layers.
DirectSynapsePersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the DirectSynapse class.
DirectSynapsePersistor() - Constructor for class org.encog.persist.persistors.DirectSynapsePersistor
disableAllCPUs() - Method in class org.encog.engine.opencl.EncogCL: Disable all devices that are CPU's.
displayDate(Date) - Static method in class org.encog.util.csv.ReadCSV: Format a date.
Distort - Class in org.encog.mathutil.randomize: A randomizer that distorts what is already present in the neural network.
Distort(double) - Constructor for class org.encog.mathutil.randomize.Distort: Construct a distort randomizer for the specified factor.
Div - Class in org.encog.bot.browse.range: A document range that represents the beginning and ending DIV tag, as well as any tages embedded between them.
Div(WebPage) - Constructor for class org.encog.bot.browse.range.Div: Construct a range to hold the DIV tag.
divide(Matrix, double) - Static method in class org.encog.mathutil.matrices.MatrixMath: Return a matrix with each cell divided by the specified value.
DocumentRange - Class in org.encog.bot.browse.range: Base class that represents a document range.
DocumentRange(WebPage) - Constructor for class org.encog.bot.browse.range.DocumentRange: Construct a document range from the specified WebPage.
dotProduct(Matrix, Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath: Compute the dot product for the two matrixes.
double2bipolar(double) - Static method in class org.encog.mathutil.matrices.BiPolarUtil: Convert a bipolar value to a boolean.
double2bipolar(double[]) - Static method in class org.encog.mathutil.matrices.BiPolarUtil: Convert a bipolar array to booleans.
double2bipolar(double[][]) - Static method in class org.encog.mathutil.matrices.BiPolarUtil: Convert a bipolar array to a boolean array.
DOUBLE_SIZE - Static variable in class org.encog.neural.data.buffer.EncogEGBFile: The size of a double.
doubleEquals(double, double) - Static method in class org.encog.mathutil.EncogMath: Determine if one double equals another, within the default percision.
DoubleGene - Class in org.encog.solve.genetic.genes: A gene that contains a floating point value.
DoubleGene() - Constructor for class org.encog.solve.genetic.genes.DoubleGene
doubleToObject(double[]) - Static method in class org.encog.engine.util.EngineArray: Convert an array of double primitives to Double objects.
downsample(Downsample, boolean, int, int, double, double) - Method in class org.encog.neural.data.image.ImageNeuralData: Downsample, and copy, the image contents into the data of this object.
downsample(int, int) - Method in class org.encog.neural.data.image.ImageNeuralDataSet: Downsample all images and generate training data.
Downsample - Interface in org.encog.util.downsample: Utility to downsample an image.
downSample(Image, int, int) - Method in interface org.encog.util.downsample.Downsample: Downsample the image to the specified height and width.
downSample(Image, int, int) - Method in class org.encog.util.downsample.RGBDownsample: Called to downsample the image and store it in the down sample component.
downSample(Image, int, int) - Method in class org.encog.util.downsample.SimpleIntensityDownsample: Called to downsample the image and store it in the down sample component.
downSampleRegion(int, int) - Method in class org.encog.util.downsample.RGBDownsample: Called to downsample a region of the image.
dumpArray(double[]) - Static method in class org.encog.util.logging.DumpMatrix: Dump an array of numbers to a string.
dumpCounts() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
DumpMatrix - Class in org.encog.util.logging: A utility for writing matrixes to the log.
dumpMatrix(Matrix) - Static method in class org.encog.util.logging.DumpMatrix: Dump a matrix to a string.
dumpWeights() - Method in class org.encog.neural.networks.BasicNetwork

E

eatWhitespace() - Method in class org.encog.parse.tags.read.ReadTags: Remove any whitespace characters that are next in the InputStream.
EG_FORMAT - Static variable in class org.encog.util.csv.CSVFormat: EG files, internally use a decimal point and comma separator.
EGAttribute - Annotation Type in org.encog.persist.annotations: This annotation is used with Encog generic persistence.
EGIgnore - Annotation Type in org.encog.persist.annotations: This annotation is used with Encog generic persistence.
EGReference - Annotation Type in org.encog.persist.annotations: This annotation is used with Encog generic persistence.
EGReferenceable - Annotation Type in org.encog.persist.annotations: This annotation is used with Encog generic persistence.
EGUnsupported - Annotation Type in org.encog.persist.annotations: This annotation is used with Encog generic persistence.
EigenvalueDecomposition - Class in org.encog.mathutil.matrices.decomposition: Eigenvalues and eigenvectors of a real matrix.
EigenvalueDecomposition(Matrix) - Constructor for class org.encog.mathutil.matrices.decomposition.EigenvalueDecomposition: Check for symmetry, then construct the eigenvalue decomposition Structure to access D and V.
ElmanPattern - Class in org.encog.neural.pattern: This class is used to generate an Elman style recurrent neural network.
ElmanPattern() - Constructor for class org.encog.neural.pattern.ElmanPattern: Create an object to generate Elman neural networks.
enableAllCPUs() - Method in class org.encog.engine.opencl.EncogCL: Enable all devices that are CPU's.
enableConnection(Synapse, int, int, boolean) - Method in class org.encog.neural.networks.BasicNetwork: Enable, or disable, a connection.
encode(int) - Method in class org.encog.mathutil.Equilateral: Get the activations for the specified set.
encode() - Method in class org.encog.neural.networks.training.genetic.NeuralGenome: Encode the neural network into genes.
encode() - Method in class org.encog.neural.networks.training.neat.NEATGenome: Convert the network to genes.
encode(NeuralDataSet, int) - Static method in class org.encog.neural.networks.training.svm.EncodeSVMProblem: Encode the Encog dataset.
encode() - Method in interface org.encog.solve.genetic.genome.Genome: Use the organism to update the genes.
ENCODE - Static variable in class org.encog.util.http.FormUtility: The charset to use for URL encoding.
encodeNetwork() - Method in interface org.encog.engine.EngineNeuralNetwork: Encode the neural network weights to an array.
encodeNetwork() - Method in class org.encog.engine.network.flat.FlatNetwork: Encode the neural network to an array of doubles.
EncodeSVMProblem - Class in org.encog.neural.networks.training.svm: Encode an Encog dataset as a SVM problem.
Encog - Class in org.encog: Main Encog class, does little more than provide version information.
ENCOG_FILE_VERSION - Static variable in class org.encog.Encog: The encog file version.
ENCOG_VERSION - Static variable in class org.encog.Encog: The version of the Encog JAR we are working with.
EncogBenchmark - Class in org.encog.util.benchmark: Benchmark Encog with several network types.
EncogBenchmark(StatusReportable) - Constructor for class org.encog.util.benchmark.EncogBenchmark: Construct a benchmark object.
EncogCL - Class in org.encog.engine.opencl: An OpenCL platform.
EncogCL() - Constructor for class org.encog.engine.opencl.EncogCL: Construct an Encog OpenCL object.
EncogCLDevice - Class in org.encog.engine.opencl: An OpenCL compute device.
EncogCLDevice(EncogCLPlatform, cl_device_id) - Constructor for class org.encog.engine.opencl.EncogCLDevice: Construct an OpenCL device.
EncogCLError - Exception in org.encog.engine.opencl: An OpenCL error.
EncogCLError(String) - Constructor for exception org.encog.engine.opencl.EncogCLError: Construct a message exception.
EncogCLError(String, Throwable) - Constructor for exception org.encog.engine.opencl.EncogCLError: Construct an exception that holds another exception.
EncogCLError(Throwable) - Constructor for exception org.encog.engine.opencl.EncogCLError: Construct an exception that holds another exception.
EncogCLItem - Class in org.encog.engine.opencl: Common data held by OpenCL devices and platforms.
EncogCLItem() - Constructor for class org.encog.engine.opencl.EncogCLItem
EncogCloud - Class in org.encog.cloud: Holds a connection to an Encog cloud.
EncogCloud() - Constructor for class org.encog.cloud.EncogCloud: Construct an Encog cloud connection to the default server at: http://cloud.encog.com/ url.
EncogCloud(String) - Constructor for class org.encog.cloud.EncogCloud: Construct an Encog cloud connection.
EncogCloudError - Exception in org.encog.cloud: Thrown when an error occurs communicating with the cloud.
EncogCloudError(String) - Constructor for exception org.encog.cloud.EncogCloudError: Construct a message exception.
EncogCloudError(String, Throwable) - Constructor for exception org.encog.cloud.EncogCloudError: Construct an exception that holds another exception.
EncogCloudError(Throwable) - Constructor for exception org.encog.cloud.EncogCloudError: Construct an exception that holds another exception.
EncogCLPlatform - Class in org.encog.engine.opencl: An Encog CL platform.
EncogCLPlatform(cl_platform_id) - Constructor for class org.encog.engine.opencl.EncogCLPlatform: Construct an OpenCL platform.
EncogCLQueue - Class in org.encog.engine.opencl: An open CL queue.
EncogCLQueue(EncogCLDevice) - Constructor for class org.encog.engine.opencl.EncogCLQueue: Construct a device.
EncogCollection - Interface in org.encog.persist: An interface to either a memory or disk-based encog collection.
EncogEGBFile - Class in org.encog.neural.data.buffer: Used to access an Encog Binary Training file (*.EGB).
EncogEGBFile(File) - Constructor for class org.encog.neural.data.buffer.EncogEGBFile: Construct an EGB file.
EncogEngine - Class in org.encog.engine: The Encog Engine.
EncogEngine() - Constructor for class org.encog.engine.EncogEngine
EncogEngineError - Exception in org.encog.engine: General error class for Encog.
EncogEngineError(String) - Constructor for exception org.encog.engine.EncogEngineError: Construct a message exception.
EncogEngineError(String, Throwable) - Constructor for exception org.encog.engine.EncogEngineError: Construct an exception that holds another exception.
EncogEngineError(Throwable) - Constructor for exception org.encog.engine.EncogEngineError: Construct an exception that holds another exception.
EncogError - Exception in org.encog: General error class for Encog.
EncogError(String) - Constructor for exception org.encog.EncogError: Construct a message exception.
EncogError(Throwable) - Constructor for exception org.encog.EncogError: Construct an exception that holds another exception.
EncogError(String, Throwable) - Constructor for exception org.encog.EncogError: Construct an exception that holds another exception.
EncogFormatter - Class in org.encog.util.logging: A simple formatter for logging.
EncogFormatter() - Constructor for class org.encog.util.logging.EncogFormatter
EncogKernel - Class in org.encog.engine.opencl.kernels: Defines a basic OpenCL kernal, as used by Encog.
EncogKernel(EncogCLDevice, String, String) - Constructor for class org.encog.engine.opencl.kernels.EncogKernel: Create an Encog OpenCL kernel.
EncogMath - Class in org.encog.mathutil: Several useful math functions for Encog.
EncogMathError - Exception in org.encog.mathutil: Thrown when a math error happens.
EncogMathError(String) - Constructor for exception org.encog.mathutil.EncogMathError: Construct a message exception.
EncogMathError(String, Throwable) - Constructor for exception org.encog.mathutil.EncogMathError: Construct an exception that holds another exception.
EncogMathError(Throwable) - Constructor for exception org.encog.mathutil.EncogMathError: Construct an exception that holds another exception.
EncogMemoryCollection - Class in org.encog.persist: A memory based collection of Encog objects.
EncogMemoryCollection() - Constructor for class org.encog.persist.EncogMemoryCollection
EncogPersistedCollection - Class in org.encog.persist: An EncogPersistedCollection holds a collection of EncogPersistedObjects.
EncogPersistedCollection(File) - Constructor for class org.encog.persist.EncogPersistedCollection: Create a persistance collection for the specified file.
EncogPersistedCollection(PersistenceLocation) - Constructor for class org.encog.persist.EncogPersistedCollection: Create an object based on the specified location.
EncogPersistedCollection(String) - Constructor for class org.encog.persist.EncogPersistedCollection: Construct an object with the specified filename.
EncogPersistedObject - Interface in org.encog.persist: This interface flags an class as being able to be persisted into an Encog collection.
EncogScript - Class in org.encog.script: Hold one Encog script program.
EncogScript() - Constructor for class org.encog.script.EncogScript
EncogScriptEngine - Interface in org.encog.script
EncogScriptEngineFactory - Class in org.encog.script
EncogScriptEngineFactory() - Constructor for class org.encog.script.EncogScriptEngineFactory
EncogScriptError - Exception in org.encog.script: General error class for Encog scripts.
EncogScriptError(String) - Constructor for exception org.encog.script.EncogScriptError: Construct a message exception.
EncogScriptError(Throwable) - Constructor for exception org.encog.script.EncogScriptError: Construct an exception that holds another exception.
EncogScriptError(String, Throwable) - Constructor for exception org.encog.script.EncogScriptError: Construct an exception that holds another exception.
EncogScriptPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the TextData class.
EncogScriptPersistor() - Constructor for class org.encog.persist.persistors.EncogScriptPersistor
EncogScriptRuntimeError - Exception in org.encog.script
EncogScriptRuntimeError(String) - Constructor for exception org.encog.script.EncogScriptRuntimeError: Construct a message exception.
EncogScriptRuntimeError(Throwable) - Constructor for exception org.encog.script.EncogScriptRuntimeError: Construct an exception that holds another exception.
EncogScriptRuntimeError(String, Throwable) - Constructor for exception org.encog.script.EncogScriptRuntimeError: Construct an exception that holds another exception.
EncogUtility - Class in org.encog.util.simple: General utility class for Encog.
EncogValidate - Class in org.encog.util: Used to validate if training is valid.
end() - Method in class org.encog.persist.PersistWriter: End the document.
endDocument() - Method in class org.encog.parse.tags.write.WriteTags: End the document.
EndIterationsStrategy - Class in org.encog.neural.networks.training.strategy.end
EndIterationsStrategy(int) - Constructor for class org.encog.neural.networks.training.strategy.end.EndIterationsStrategy
endLoad() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: This method should be called once all the data has been loaded.
EndMaxErrorStrategy - Class in org.encog.neural.networks.training.strategy.end
EndMaxErrorStrategy(double) - Constructor for class org.encog.neural.networks.training.strategy.end.EndMaxErrorStrategy
EndMinutesStrategy - Class in org.encog.neural.networks.training.strategy.end
EndMinutesStrategy(int) - Constructor for class org.encog.neural.networks.training.strategy.end.EndMinutesStrategy
endObjects() - Method in class org.encog.persist.PersistWriter: End the objects collection.
endTag() - Method in class org.encog.parse.tags.write.WriteTags: End the current tag.
endTag(String) - Method in class org.encog.parse.tags.write.WriteTags: End a tag, require that we are ending the specified tag.
EndTrainingStrategy - Interface in org.encog.neural.networks.training.strategy.end
enforceLimit() - Method in class org.encog.neural.networks.structure.NeuralStructure: Enforce that all connections are above the connection limit.
EngineArray - Class in org.encog.engine.util: Some array functions used by Encog.
EngineConcurrency - Class in org.encog.engine.concurrency: This class abstracts thread pools, and potentially grids and other types of concurrency.
EngineConcurrency() - Constructor for class org.encog.engine.concurrency.EngineConcurrency: Construct a concurrency object.
EngineData - Interface in org.encog.engine.data: Training data is stored in two ways, depending on if the data is for supervised, or unsupervised training.
EngineDataSet - Interface in org.encog.engine.data: An interface designed to abstract classes that store machine learning data.
EngineIndexableSet - Interface in org.encog.engine.data: Specifies that a data set can be accessed in random order via an index.
EngineMachineLearning - Interface in org.encog.engine: Generic interface to a Machine Learning class, such as a neural network or SVM.
EngineNeuralNetwork - Interface in org.encog.engine: An interface that defines a neural network.
EngineTask - Interface in org.encog.engine.concurrency: An individual task that can be submitted to the EncogCurrency utility.
ENGLISH - Static variable in class org.encog.util.csv.CSVFormat: Decimal point is typically used in English speaking counties.
EnglishTimeUnitNames - Class in org.encog.util.time: Class used to get the English names for TimeUnits.
EnglishTimeUnitNames() - Constructor for class org.encog.util.time.EnglishTimeUnitNames
eps - Variable in class org.encog.mathutil.libsvm.svm_parameter
EPSILON_SVR - Static variable in class org.encog.mathutil.libsvm.svm_parameter
equal(Layer, Layer) - Method in class org.encog.neural.networks.structure.LayerComparator: Determine if two layers are equal.
equals(Matrix, int) - Method in class org.encog.mathutil.matrices.Matrix: Compare to matrixes with the specified level of precision.
equals(Object) - Method in class org.encog.mathutil.matrices.Matrix: Check to see if this matrix equals another, using default precision.
equals(Object) - Method in class org.encog.neural.data.market.TickerSymbol
equals(BasicNetwork) - Method in class org.encog.neural.networks.BasicNetwork: Compare the two neural networks.
equals(BasicNetwork, int) - Method in class org.encog.neural.networks.BasicNetwork: Determine if this neural network is equal to another.
equals(BasicNetwork) - Method in interface org.encog.neural.networks.Network: Compare the two neural networks.
equals(BasicNetwork, int) - Method in interface org.encog.neural.networks.Network: Determine if this neural network is equal to another.
equals(BasicNetwork, BasicNetwork, int) - Static method in class org.encog.neural.networks.structure.NetworkCODEC: Determine if the two neural networks are equal.
equals(BasicNetwork, BasicNetwork) - Static method in class org.encog.neural.networks.structure.NetworkCODEC: Determine if the two neural networks are equal.
equals(Object) - Method in class org.encog.persist.DirectoryEntry
equals(Object) - Method in class org.encog.solve.genetic.genes.IntegerGene
Equilateral - Class in org.encog.mathutil: Used to produce an array of activations to classify data into groups.
Equilateral(int, double, double) - Constructor for class org.encog.mathutil.Equilateral: Construct an equilateral matrix.
ERROR - Static variable in class org.encog.neural.networks.layers.ContextLayer
ERROR_ADD - Static variable in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Error message for ADD.
ERROR_REMOVE - Static variable in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Error message for REMOVE.
ErrorCalculation - Class in org.encog.engine.util: Calculate the error of a neural network.
ErrorCalculation() - Constructor for class org.encog.engine.util.ErrorCalculation
ErrorCalculationMode - Enum in org.encog.engine.util: Selects the error calculation mode for Encog.
establishEquilibrium() - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Run the network until thermal equilibrium is established.
EULERS_NUMBER - Static variable in class org.encog.mathutil.MathConst: Euler's number.
Evaluate - Class in org.encog.util.benchmark: Used to evaluate the training time for a network.
Evaluate() - Constructor for class org.encog.util.benchmark.Evaluate
evaluate(BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.simple.EncogUtility: Evaluate the network and display (to the console) the output for every value in the training set.
evaluateTrain(int, int, int, int) - Static method in class org.encog.util.benchmark.Evaluate
evaluateTrain(EncogCLDevice, int, int, int, int) - Static method in class org.encog.util.benchmark.Evaluate
evaluateTrain(OpenCLTrainingProfile, BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.benchmark.Evaluate: Evaluate how long it takes to calculate the error for the network.
ExcelCODEC - Class in org.encog.neural.data.buffer.codec: A CODEC that can read/write Microsoft Excel (*.XLSX) files.
ExcelCODEC(File) - Constructor for class org.encog.neural.data.buffer.codec.ExcelCODEC: Constructor to create Excel from binary.
ExcelCODEC(File, int, int) - Constructor for class org.encog.neural.data.buffer.codec.ExcelCODEC: Create a CODEC to load data from Excel to binary.
execute(EncogKernel) - Method in class org.encog.engine.opencl.EncogCLQueue: Execute the specified kernel.
exists(String) - Method in interface org.encog.persist.EncogCollection: Determine if the specified key exists.
exists(String) - Method in class org.encog.persist.EncogMemoryCollection: Determine if the specified key exists.
exists(String) - Method in class org.encog.persist.EncogPersistedCollection: Determine if the specified resource exists.
exists() - Method in class org.encog.persist.location.FilePersistence
exists() - Method in class org.encog.persist.location.InputStreamPersistence: Because this is based on a stream, it always exists, so return true.
exists() - Method in class org.encog.persist.location.OutputStreamPersistence
exists() - Method in interface org.encog.persist.location.PersistenceLocation
exists() - Method in class org.encog.persist.location.ResourcePersistence: Exist is not supported for resource persistence.
exp(double) - Static method in class org.encog.engine.util.BoundMath: Calculate the exp.
external2Binary(File) - Method in class org.encog.neural.data.buffer.BinaryDataLoader: Convert an external file format, such as CSV, to the Encog binary training format.
extract(String, String, String, int) - Static method in class org.encog.bot.BotUtil: This method is very useful for grabbing information from a HTML page.
extractFromIndex(String, String, String, int, int) - Static method in class org.encog.bot.BotUtil: This method is very useful for grabbing information from a HTML page.

F

FanInRandomizer - Class in org.encog.mathutil.randomize: A randomizer that attempts to create starting weight values that are conducive to propagation training.
FanInRandomizer() - Constructor for class org.encog.mathutil.randomize.FanInRandomizer: Create a fan-in randomizer with default values.
FanInRandomizer(double, boolean) - Constructor for class org.encog.mathutil.randomize.FanInRandomizer: Construct a fan-in randomizer along the specified boundary.
FanInRandomizer(double, double, boolean) - Constructor for class org.encog.mathutil.randomize.FanInRandomizer: Construct a fan-in randomizer.
FeedforwardLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for an Feedforward type network.
FeedforwardLogic() - Constructor for class org.encog.neural.networks.logic.FeedforwardLogic
FeedForwardPattern - Class in org.encog.neural.pattern: Used to create feedforward neural networks.
FeedForwardPattern() - Constructor for class org.encog.neural.pattern.FeedForwardPattern
FieldMapping - Class in org.encog.persist.persistors.generic: A simple mapping that holds the reference, field and target of an object.
FieldMapping(int, Field, Object) - Constructor for class org.encog.persist.persistors.generic.FieldMapping: Construct a field mapping.
FilePersistence - Class in org.encog.persist.location: A persistence location based on a file.
FilePersistence(File) - Constructor for class org.encog.persist.location.FilePersistence: Construct a persistance location based on a file.
fill(double[], double) - Static method in class org.encog.engine.util.EngineArray: Fill a double array.
fill(float[], float) - Static method in class org.encog.engine.util.EngineArray: Fill a float array.
finalizeStructure() - Method in class org.encog.neural.networks.structure.NeuralStructure: Build the synapse and layer structure.
find(Class<?>, int) - Method in class org.encog.bot.browse.WebPage: Find the specified DocumentRange subclass in the contents list.
find(DirectoryEntry) - Method in interface org.encog.persist.EncogCollection: Find the object that corresponds to the specified directory entry, return null, if not found.
find(String) - Method in interface org.encog.persist.EncogCollection: Find the object that corresponds to the specified key.
find(DirectoryEntry) - Method in class org.encog.persist.EncogMemoryCollection: Find the object that corresponds to the specified directory entry, return null, if not found.
find(String) - Method in class org.encog.persist.EncogMemoryCollection: Find the object that corresponds to the specified key.
find(DirectoryEntry) - Method in class org.encog.persist.EncogPersistedCollection: Find the specified object, using a DirectoryEntry.
find(String) - Method in class org.encog.persist.EncogPersistedCollection: Called to search all Encog objects in this collection for one with a name that passes what was passed in.
findBounds() - Method in interface org.encog.util.downsample.Downsample: Find the bounds around the image to exclude whitespace.
findBounds() - Method in class org.encog.util.downsample.RGBDownsample: This method is called to automatically crop the image so that whitespace is removed.
FindCPN - Class in org.encog.neural.networks.training.cpn: Find the parts of a CPN network.
FindCPN(BasicNetwork) - Constructor for class org.encog.neural.networks.training.cpn.FindCPN: Construct the object and find the parts of the network.
findEndTag(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage: Find the end tag that lines up to the beginning tag.
findField(Class<?>, String) - Static method in class org.encog.util.obj.ReflectionUtil: Find the specified field, look also in superclasses.
findInputField(Class<?>, int) - Method in class org.encog.normalize.DataNormalization: Find an input field by its class.
findLink(String) - Method in class org.encog.bot.browse.WebPage: Find the link that contains the specified string.
findNextSynapseByLayerType(Layer, Class<? extends Layer>) - Method in class org.encog.neural.networks.structure.NeuralStructure: Find the next synapse by layer type.
findOccurance(String, String, int) - Static method in class org.encog.bot.BotUtil: Find the specified occurrence of one string in another string.
findOutputField(Class<?>, int) - Method in class org.encog.normalize.DataNormalization: Find an output field by its class.
findPreviousSynapseByLayerType(Layer, Class<? extends Layer>) - Method in class org.encog.neural.networks.structure.NeuralStructure: Find previous synapse by layer type.
findStringInArray(String[], String) - Static method in class org.encog.engine.util.EngineArray: Search for a string in an array.
findSynapse(Layer, Layer, boolean) - Method in class org.encog.neural.networks.structure.NeuralStructure: Find the specified synapse, throw an error if it is required.
findTag(String, boolean) - Method in class org.encog.parse.tags.read.ReadXML: Advance until the specified tag is found.
findType(String, int) - Method in class org.encog.bot.browse.range.Form: Find the form input by type.
finish() - Method in class org.encog.neural.networks.training.TrainingStatusUtility: Report that we are finished.
finishTraining() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Training is to stop, free any resources.
finishTraining() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Training is to stop, free any resources.
finishTraining() - Method in interface org.encog.engine.network.train.TrainFlatNetwork: Training is to stop, free any resources.
finishTraining() - Method in class org.encog.neural.networks.training.BasicTraining: Should be called after training has completed and the iteration method will not be called any further.
finishTraining() - Method in class org.encog.neural.networks.training.neat.NEATTraining: Called when training is done.
finishTraining() - Method in class org.encog.neural.networks.training.propagation.Propagation: Should be called after training has completed and the iteration method will not be called any further.
finishTraining() - Method in class org.encog.neural.networks.training.svm.SVMTrain: Called to finish training.
finishTraining() - Method in interface org.encog.neural.networks.training.Train: Should be called once training is complete and no more iterations are needed.
FIRST_LAMBDA - Static variable in class org.encog.engine.network.train.prop.TrainFlatNetworkSCG: The starting value for lambda.
FIRST_SIGMA - Static variable in class org.encog.engine.network.train.prop.TrainFlatNetworkSCG: The starting value for sigma.
FlatGradientWorker - Interface in org.encog.engine.network.train.gradient: An interface used to define gradient workers for flat networks.
FlatLayer - Class in org.encog.engine.network.flat: Used to configure a flat layer.
FlatLayer(ActivationFunction, int, double, double[]) - Constructor for class org.encog.engine.network.flat.FlatLayer: Construct a flat layer.
FlatNetwork - Class in org.encog.engine.network.flat: Implements a flat (vector based) neural network in the Encog Engine.
FlatNetwork() - Constructor for class org.encog.engine.network.flat.FlatNetwork: Default constructor.
FlatNetwork(FlatLayer[]) - Constructor for class org.encog.engine.network.flat.FlatNetwork: Create a flat network from an array of layers.
FlatNetwork(int, int, int, int, boolean) - Constructor for class org.encog.engine.network.flat.FlatNetwork: Construct a flat neural network.
FlatNetworkRBF - Class in org.encog.engine.network.flat: A flat network designed to handle an RBF.
FlatNetworkRBF() - Constructor for class org.encog.engine.network.flat.FlatNetworkRBF: Default constructor.
FlatNetworkRBF(int, int, int, RadialBasisFunction[]) - Constructor for class org.encog.engine.network.flat.FlatNetworkRBF: Construct an RBF flat network.
flatten() - Method in class org.encog.neural.networks.structure.NeuralStructure: Flatten the network.
flattenWeights() - Method in class org.encog.neural.networks.structure.NeuralStructure: Flatten the weights, do not restructure.
FlatUpdateNeeded - Enum in org.encog.neural.networks.structure: Is a flat update needed?
fold(int) - Method in class org.encog.neural.data.folded.FoldedDataSet: Fold the dataset.
FoldedDataSet - Class in org.encog.neural.data.folded: A folded data set allows you to "fold" the data into several equal(or nearly equal) datasets.
FoldedDataSet(Indexable) - Constructor for class org.encog.neural.data.folded.FoldedDataSet: Create a folded dataset.
FoldedIterator - Class in org.encog.neural.data.folded: Used to iterate over a folded data set.
FoldedIterator(FoldedDataSet) - Constructor for class org.encog.neural.data.folded.FoldedIterator: Construct the folded iterator.
Form - Class in org.encog.bot.browse.range: A document range that represents a form, and all embedded tags.
Form(WebPage) - Constructor for class org.encog.bot.browse.range.Form: Construct a form on the specified web page.
Form.Method - Enum in org.encog.bot.browse.range: The method for this form.
Format - Class in org.encog.engine.util: Provides the ability for Encog to format numbers and times.
format(double, int) - Method in class org.encog.util.csv.CSVFormat: Format the specified number to a string with the specified number of fractional digits.
format(LogRecord) - Method in class org.encog.util.logging.EncogFormatter: Format the log record.
formatDouble(double, int) - Static method in class org.encog.engine.util.Format: Format a double.
formatInteger(int) - Static method in class org.encog.engine.util.Format: Format an integer.
formatMemory(long) - Static method in class org.encog.engine.util.Format: Format a memory amount, to something like 32 MB.
formatNeuralData(NeuralData) - Static method in class org.encog.util.simple.EncogUtility: Format neural data as a list of numbers.
formatPercent(double) - Static method in class org.encog.engine.util.Format: Format a percent.
formatPercentWhole(double) - Static method in class org.encog.engine.util.Format: Format a percent with no decimal places.
formatTimeSpan(int) - Static method in class org.encog.engine.util.Format: Format a time span as seconds, minutes, hours and days.
FormElement - Class in org.encog.bot.browse.range: A document range that represents one individual component to a form.
FormElement(WebPage) - Constructor for class org.encog.bot.browse.range.FormElement: Construct a form element from the specified web page.
FormUtility - Class in org.encog.util.http: This class is used to construct responses to HTML forms.
FormUtility(OutputStream, String) - Constructor for class org.encog.util.http.FormUtility: Prepare to access either a regular, or multipart, form.
fromList(CSVFormat, String) - Static method in class org.encog.util.csv.NumberList: Get an array of double's from a string of comma separated text.
fromPackedArray(Double[], int) - Method in class org.encog.mathutil.matrices.Matrix: Create a matrix from a packed array.
function(int, int) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodBubble: Determine how much the current neuron should be affected by training based on its proximity to the winning neuron.
function(int, int) - Method in interface org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodFunction: Determine how much the current neuron should be affected by training based on its proximity to the winning neuron.
function(int, int) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodRBF: Calculate the value for the multi RBF function.
function(int, int) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingle: Determine how much the current neuron should be affected by training based on its proximity to the winning neuron.
function(int, int) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingleRBF: Determine how much the current neuron should be affected by training based on its proximity to the winning neuron.

G

gamma - Variable in class org.encog.mathutil.libsvm.svm_parameter
GaussianFunction - Class in org.encog.mathutil.rbf: Multi-dimensional gaussian function.
GaussianFunction() - Constructor for class org.encog.mathutil.rbf.GaussianFunction: Default constructor, used for reflection.
GaussianFunction(double, double, double) - Constructor for class org.encog.mathutil.rbf.GaussianFunction: Construct a single-dimension Gaussian function with the specified peak, centers and widths.
GaussianFunction(double, double[], double) - Constructor for class org.encog.mathutil.rbf.GaussianFunction: Construct a multi-dimension Gaussian function with the specified peak, centers and widths.
GaussianFunction(int) - Constructor for class org.encog.mathutil.rbf.GaussianFunction: Create centered at zero, width 0, and peak 0.
GaussianRandomizer - Class in org.encog.mathutil.randomize: Generally, you will not want to use this randomizer as a pure neural network randomizer.
GaussianRandomizer(double, double) - Constructor for class org.encog.mathutil.randomize.GaussianRandomizer: Construct a Gaussian randomizer.
Gene - Interface in org.encog.solve.genetic.genes: Describes a gene.
GENERAL_ERROR - Static variable in class org.encog.persist.EncogPersistedCollection: Generic error message for bad XML.
generate() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Generate the training sets.
generate() - Method in class org.encog.neural.pattern.ADALINEPattern: Generate the network.
generate() - Method in class org.encog.neural.pattern.ART1Pattern: Generate the neural network.
generate() - Method in class org.encog.neural.pattern.BAMPattern
generate() - Method in class org.encog.neural.pattern.BoltzmannPattern: Generate the network.
generate() - Method in class org.encog.neural.pattern.CPNPattern: Generate the network.
generate() - Method in class org.encog.neural.pattern.ElmanPattern: Generate the Elman neural network.
generate() - Method in class org.encog.neural.pattern.FeedForwardPattern: Generate the feedforward neural network.
generate() - Method in class org.encog.neural.pattern.HopfieldPattern: Generate the Hopfield neural network.
generate() - Method in class org.encog.neural.pattern.JordanPattern: Generate a Jordan neural network.
generate() - Method in class org.encog.neural.pattern.NEATPattern: Generate the RBF network.
generate() - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Generate the specified neural network.
generate() - Method in class org.encog.neural.pattern.RadialBasisPattern: Generate the RBF network.
generate() - Method in class org.encog.neural.pattern.RSOMPattern: Generate the RSOM network.
generate() - Method in class org.encog.neural.pattern.SOMPattern: Generate the RSOM network.
generate() - Method in class org.encog.neural.pattern.SVMPattern
generate(long, int, int, int, double, double) - Static method in class org.encog.util.benchmark.RandomTrainingFactory: Generate a random training set.
generate(NeuralDataSet, long, int, double, double) - Static method in class org.encog.util.benchmark.RandomTrainingFactory: Generate random training into a training set.
generate() - Method in class org.encog.util.identity.BasicGenerateID: Generate the next ID.
generate() - Method in interface org.encog.util.identity.GenerateID: Generate the next ID.
GenerateClasslist - Class in org.encog.util.obj: Utility to automatically generate the Encog class list file.
GenerateClasslist() - Constructor for class org.encog.util.obj.GenerateClasslist
GenerateID - Interface in org.encog.util.identity: Interface that defines a unique ID generator.
generateInputForPrediction(Date) - Method in class org.encog.neural.data.market.MarketNeuralDataSet: To be implemented later.
generateInputNeuralData(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Generate input neural data for the specified index.
generateOutputNeuralData(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Generate neural ideal data for the specified index.
GenericPersistor - Class in org.encog.persist.persistors.generic: An Encog perisistor that can be used with any object that supports the Encog generic persistence.
GenericPersistor(Class<?>) - Constructor for class org.encog.persist.persistors.generic.GenericPersistor: Construct a generic persistor for the specified class.
GeneticAlgorithm - Class in org.encog.solve.genetic: Implements a genetic algorithm.
GeneticAlgorithm() - Constructor for class org.encog.solve.genetic.GeneticAlgorithm
GeneticError - Exception in org.encog.solve.genetic: An error raised by the genetic algorithm.
GeneticError(String) - Constructor for exception org.encog.solve.genetic.GeneticError: Construct a message exception.
GeneticError(String, Throwable) - Constructor for exception org.encog.solve.genetic.GeneticError: Construct an exception that holds another exception.
GeneticError(Throwable) - Constructor for exception org.encog.solve.genetic.GeneticError: Construct an exception that holds another exception.
GeneticScoreAdapter - Class in org.encog.neural.networks.training.genetic: This adapter allows a CalculateScore object to be used to calculate a Genome's score, where a CalculateGenomeScore object would be called for.
GeneticScoreAdapter(CalculateScore) - Constructor for class org.encog.neural.networks.training.genetic.GeneticScoreAdapter: Construct the adapter.
Genome - Interface in org.encog.solve.genetic.genome: A genome is the basic blueprint for creating an organism in Encog.
GenomeComparator - Class in org.encog.solve.genetic.genome: Used to compare two genomes, a score object is used.
GenomeComparator(CalculateGenomeScore) - Constructor for class org.encog.solve.genetic.genome.GenomeComparator: Construct the genome comparator.
get(int, int) - Method in class org.encog.mathutil.matrices.Matrix: Read the specified cell in the matrix.
get(String) - Method in class org.encog.neural.data.PropertyData: Get the specified property.
get(String) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation: Get an object by name.
get(int) - Method in class org.encog.solve.genetic.genome.Chromosome: Get an individual gene.
get(int) - Method in class org.encog.solve.genetic.innovation.BasicInnovationList: Get a specific innovation, by index.
get(int) - Method in interface org.encog.solve.genetic.innovation.InnovationList: Get the innovation specified by index.
get(int) - Method in class org.encog.solve.genetic.population.BasicPopulation: Get a genome by index.
get(int) - Method in interface org.encog.solve.genetic.population.Population: Get a genome by index.
get(int) - Method in class org.encog.util.csv.ReadCSV: Get the specified column as a string.
get(String) - Method in class org.encog.util.csv.ReadCSV: Get the column by its string name, as a string.
getA() - Method in class org.encog.engine.util.ObjectPair
getA1() - Method in class org.encog.neural.networks.logic.ART1Logic
getA1() - Method in class org.encog.neural.pattern.ART1Pattern
getAction() - Method in class org.encog.bot.browse.range.Form
getActivation() - Method in class org.encog.engine.network.flat.FlatLayer
getActivationFunction() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
getActivationFunction() - Method in class org.encog.neural.networks.layers.BasicLayer
getActivationFunction() - Method in interface org.encog.neural.networks.layers.Layer
getActivationFunction() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getActivationFunctions() - Method in class org.encog.engine.network.flat.FlatNetwork
getActivationResponse() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getActivationResponse() - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene
getAdjustedScore() - Method in class org.encog.solve.genetic.genome.BasicGenome
getAdjustedScore() - Method in interface org.encog.solve.genetic.genome.Genome: Get the adjusted score, this considers old-age penalties and youth bonuses.
getAge() - Method in class org.encog.solve.genetic.species.BasicSpecies
getAge() - Method in interface org.encog.solve.genetic.species.Species
getAllFields(Class<?>) - Static method in class org.encog.util.obj.ReflectionUtil: Get all of the fields from the specified class as a collection.
getAllFields(Class<?>, Collection<Field>) - Static method in class org.encog.util.obj.ReflectionUtil: Get all of the fields in the specified class and super classes.
getAllValues() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
getAmountToSpawn() - Method in class org.encog.solve.genetic.genome.BasicGenome
getAmountToSpawn() - Method in interface org.encog.solve.genetic.genome.Genome
getAnnealCycles() - Method in class org.encog.neural.pattern.BoltzmannPattern
getArray() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Get the network as an array of doubles.
getArray() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Used to pass the getArray call on to the parent object.
getArray() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Subclasses must provide access to an array that makes up the solution.
getArrayCopy() - Method in class org.encog.mathutil.matrices.Matrix
getArrayCopy() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
getArrayCopy() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Used to pass the getArrayCopy call on to the parent object.
getArrayCopy() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Get a copy of the array.
getAttributeInt(String) - Method in class org.encog.parse.tags.Tag: Get the specified attribute as an integer.
getAttributes() - Method in class org.encog.bot.rss.RSS: Get the list of attributes.
getAttributes() - Method in class org.encog.parse.tags.Tag: Get a map of all attributes.
getAttributeValue(String) - Method in class org.encog.parse.tags.Tag: Get the value of the specified attribute.
getB() - Method in class org.encog.engine.util.ObjectPair
getB1() - Method in class org.encog.neural.networks.logic.ART1Logic
getB1() - Method in class org.encog.neural.pattern.ART1Pattern
getBegin() - Method in class org.encog.bot.browse.range.DocumentRange
getBeginTraining() - Method in class org.encog.engine.network.flat.FlatNetwork
getBest() - Method in class org.encog.solve.genetic.population.BasicPopulation
getBest() - Method in interface org.encog.solve.genetic.population.Population
getBestNetwork() - Method in class org.encog.neural.prune.PruneIncremental
getBestScore() - Method in class org.encog.solve.genetic.species.BasicSpecies
getBestScore() - Method in interface org.encog.solve.genetic.species.Species
getBias() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
getBiasActivation() - Method in class org.encog.engine.network.flat.FlatLayer
getBiasActivation() - Method in class org.encog.neural.networks.layers.BasicLayer
getBiasActivation() - Method in interface org.encog.neural.networks.layers.Layer: Most layer types will default this value to one.
getBiasValues() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
getBiasWeight(int) - Method in class org.encog.neural.networks.layers.BasicLayer: Get an bias weight value.
getBiasWeight(int) - Method in class org.encog.neural.networks.layers.ContextLayer: Get one weight bias value.
getBiasWeight(int) - Method in interface org.encog.neural.networks.layers.Layer: Get an bias weight value.
getBiasWeights() - Method in class org.encog.neural.networks.layers.BasicLayer
getBiasWeights() - Method in class org.encog.neural.networks.layers.ContextLayer
getBiasWeights() - Method in interface org.encog.neural.networks.layers.Layer
getBinaryScore() - Method in class org.encog.util.benchmark.EncogBenchmark
getBoolean(int) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Get the specified data item as a boolean.
getBoundary() - Static method in class org.encog.util.http.FormUtility: Generate a boundary for a multipart form.
getC1() - Method in class org.encog.neural.networks.logic.ART1Logic
getC1() - Method in class org.encog.neural.pattern.ART1Pattern
getCalc() - Method in class org.encog.engine.concurrency.calc.CalcOpenCLDevice
getCalculateScore() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
getCalculateScore() - Method in class org.encog.solve.genetic.GeneticAlgorithm
getCalculateScore() - Method in class org.encog.solve.genetic.genome.GenomeComparator
getCatchAll() - Method in class org.encog.normalize.output.mapped.OutputFieldEncode
getCenter() - Method in class org.encog.engine.network.activation.ActivationStep
getCenter(int) - Method in interface org.encog.engine.network.rbf.RadialBasisFunction: Get the center of this RBD.
getCenter(int) - Method in class org.encog.mathutil.rbf.BasicRBF: Get the center of this RBD.
getCenters() - Method in interface org.encog.engine.network.rbf.RadialBasisFunction
getCenters() - Method in class org.encog.mathutil.rbf.BasicRBF
getChromosomes() - Method in class org.encog.solve.genetic.genome.BasicGenome
getChromosomes() - Method in interface org.encog.solve.genetic.genome.Genome
getCL() - Method in class org.encog.Encog
getCL() - Method in class org.encog.engine.EncogEngine
getClassAttribute() - Method in class org.encog.bot.browse.range.DocumentRange
getCloud() - Method in class org.encog.cloud.CloudTask
getCloud() - Method in class org.encog.neural.networks.training.BasicTraining
getCloud() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getCloud() - Method in interface org.encog.neural.networks.training.Train
getClScore() - Method in class org.encog.util.benchmark.EncogBenchmark
getCLSource() - Method in class org.encog.engine.opencl.kernels.EncogKernel
getCode() - Method in class org.encog.bot.dataunit.CodeDataUnit
getCodec() - Method in class org.encog.neural.data.buffer.BinaryDataLoader
getCol(int) - Method in class org.encog.mathutil.matrices.Matrix: Read one entire column from the matrix as a sub-matrix.
getCollection() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
getCollection() - Method in class org.encog.neural.networks.layers.BasicLayer
getCollection() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getCollection() - Method in class org.encog.persist.BasicPersistedObject
getCollection() - Method in class org.encog.persist.BasicPersistedSubObject: Not implemented.
getCollection() - Method in interface org.encog.persist.EncogPersistedObject
getCollection() - Method in class org.encog.solve.genetic.population.BasicPopulation
getCols() - Method in class org.encog.mathutil.matrices.Matrix: Get the columns in the matrix.
getColumnCount() - Method in class org.encog.util.csv.ReadCSV: Get the column count.
getCommands() - Method in class org.encog.engine.opencl.EncogCLQueue
getComparator() - Method in class org.encog.solve.genetic.GeneticAlgorithm
getCompatibilityScore(NEATGenome) - Method in class org.encog.neural.networks.training.neat.NEATGenome: Get the compatibility score with another genome.
getConnection() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
getConnectionLimit() - Method in class org.encog.engine.network.flat.FlatNetwork
getConnectionLimit() - Method in class org.encog.neural.networks.structure.NeuralStructure
getConsoleHandler() - Static method in class org.encog.util.logging.Logging
getConstBegin() - Method in class org.encog.neural.networks.training.svm.SVMTrain
getConstEnd() - Method in class org.encog.neural.networks.training.svm.SVMTrain
getConstStep() - Method in class org.encog.neural.networks.training.svm.SVMTrain
getContectCount() - Method in class org.encog.engine.network.flat.FlatLayer
getContents() - Method in class org.encog.bot.browse.WebPage
getContents() - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
getContents() - Method in class org.encog.persist.EncogMemoryCollection
getContext() - Method in class org.encog.engine.opencl.EncogCLPlatform
getContext() - Method in class org.encog.engine.opencl.kernels.EncogKernel
getContext() - Method in class org.encog.neural.networks.layers.ContextLayer
getContextFedBy() - Method in class org.encog.engine.network.flat.FlatLayer
getContextTargetOffset() - Method in class org.encog.engine.network.flat.FlatNetwork
getContextTargetSize() - Method in class org.encog.engine.network.flat.FlatNetwork
getCount() - Method in class org.encog.engine.network.flat.FlatLayer
getCount() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
getCpuScore() - Method in class org.encog.util.benchmark.EncogBenchmark
getCrossover() - Method in class org.encog.solve.genetic.GeneticAlgorithm
getCSVFormat() - Method in class org.encog.normalize.DataNormalization
getCurrentBlue() - Method in class org.encog.util.downsample.RGBDownsample
getCurrentFlatNetwork() - Method in class org.encog.neural.networks.training.propagation.Propagation
getCurrentFold() - Method in class org.encog.neural.data.folded.FoldedDataSet
getCurrentFoldOffset() - Method in class org.encog.neural.data.folded.FoldedDataSet
getCurrentFoldSize() - Method in class org.encog.neural.data.folded.FoldedDataSet
getCurrentGreen() - Method in class org.encog.util.downsample.RGBDownsample
getCurrentIndex() - Method in class org.encog.normalize.segregate.index.IndexSegregator
getCurrentPage() - Method in class org.encog.bot.browse.Browser
getCurrentRed() - Method in class org.encog.util.downsample.RGBDownsample
getCurrentState() - Method in class org.encog.neural.networks.logic.ThermalLogic
getCurrentValue() - Method in class org.encog.normalize.input.BasicInputField
getCurrentValue() - Method in interface org.encog.normalize.input.InputField
getCycles() - Method in class org.encog.solve.anneal.SimulatedAnnealing
getD() - Method in class org.encog.mathutil.matrices.decomposition.EigenvalueDecomposition: Return the block diagonal eigenvalue matrix
getD1() - Method in class org.encog.neural.networks.logic.ART1Logic
getD1() - Method in class org.encog.neural.pattern.ART1Pattern
getData() - Method in class org.encog.bot.browse.WebPage
getData() - Method in class org.encog.engine.data.BasicEngineDataSet: Get the data held by this container.
getData() - Method in class org.encog.mathutil.matrices.Matrix
getData() - Method in class org.encog.neural.data.basic.BasicNeuralData: Get the data as an array.
getData(int) - Method in class org.encog.neural.data.basic.BasicNeuralData: Get a data value at the specified index.
getData() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Get the data held by this container.
getData() - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Get the data held by this object as an array of doubles.
getData(int) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Get the data held by the index.
getData(MarketDataType) - Method in class org.encog.neural.data.market.loader.LoadedMarketData: Get one type of market data from this date.
getData() - Method in interface org.encog.neural.data.NeuralData
getData(int) - Method in interface org.encog.neural.data.NeuralData: Get the element specified index value.
getData() - Method in class org.encog.neural.data.PropertyData: Get all of the property data as a map.
getData() - Method in class org.encog.neural.data.temporal.TemporalPoint
getData(int) - Method in class org.encog.neural.data.temporal.TemporalPoint: Get the data at the specified index.
getDataset() - Method in class org.encog.normalize.target.NormalizationStorageNeuralDataSet
getDataSize() - Method in class org.encog.bot.browse.WebPage: Get the number of data items in this collection.
getDataType() - Method in class org.encog.neural.data.market.MarketDataDescription
getDataUnit(int) - Method in class org.encog.bot.browse.WebPage: Get the DataUnit unit at the specified index.
getDate() - Method in class org.encog.bot.rss.RSSItem: Get the publication date.
getDate(String) - Method in class org.encog.neural.data.PropertyData: Get a property as a date.
getDate(String) - Method in class org.encog.util.csv.ReadCSV: Get the column as a date.
getDecimal() - Method in class org.encog.util.csv.CSVFormat
getDecimalCharacter() - Static method in class org.encog.util.csv.CSVFormat: Get the decimal character currently in use by the computer's default location.
getDepth(Layer) - Method in class org.encog.neural.networks.structure.CalculateDepth: Get the depth for a specific layer.
getDescription() - Method in class org.encog.bot.rss.RSSItem: Get the description.
getDescription() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
getDescription() - Method in class org.encog.neural.networks.layers.BasicLayer
getDescription() - Method in interface org.encog.neural.networks.Network
getDescription() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getDescription() - Method in class org.encog.persist.BasicPersistedObject
getDescription() - Method in class org.encog.persist.BasicPersistedSubObject: Not implemented.
getDescription() - Method in class org.encog.persist.DirectoryEntry
getDescription() - Method in interface org.encog.persist.EncogPersistedObject
getDescription() - Method in class org.encog.solve.genetic.population.BasicPopulation
getDescriptions() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getDesiredSetSize() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getDevice() - Method in class org.encog.engine.concurrency.calc.CalcOpenCLDevice
getDevice() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getDevice() - Method in class org.encog.engine.opencl.EncogCLDevice
getDevice() - Method in class org.encog.engine.opencl.EncogCLQueue
getDevice() - Method in class org.encog.engine.opencl.kernels.EncogKernel
getDevice() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerOpenCL
getDevice() - Method in class org.encog.util.benchmark.EncogBenchmark
getDeviceLong(int) - Method in class org.encog.engine.opencl.EncogCLDevice: Get a long param from the device.
getDevices() - Method in class org.encog.engine.opencl.EncogCL
getDevices() - Method in class org.encog.engine.opencl.EncogCLPlatform
getDeviceString(int) - Method in class org.encog.engine.opencl.EncogCLDevice: Get a config string from the device.
getDimensions() - Method in interface org.encog.engine.network.rbf.RadialBasisFunction
getDimensions() - Method in class org.encog.mathutil.rbf.BasicRBF
getDirectory() - Method in interface org.encog.persist.EncogCollection
getDirectory() - Method in class org.encog.persist.EncogMemoryCollection
getDirectory() - Method in class org.encog.persist.EncogPersistedCollection
getDisabledConnections() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
getDistance(double[], int) - Method in class org.encog.mathutil.Equilateral: Get the Euclidean distance between the specified data and the set number.
getDouble(String) - Method in class org.encog.neural.data.PropertyData: Get a property as a double.
getDouble(int) - Method in class org.encog.util.csv.ReadCSV: Get the column as a double specified by index.
getDouble(String) - Method in class org.encog.util.csv.ReadCSV: Get the specified column as a double.
getDoublePivot() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition: Return pivot permutation vector as a one-dimensional double array
getDownSampleBottom() - Method in interface org.encog.util.downsample.Downsample
getDownSampleBottom() - Method in class org.encog.util.downsample.RGBDownsample
getDownSampleLeft() - Method in interface org.encog.util.downsample.Downsample
getDownSampleLeft() - Method in class org.encog.util.downsample.RGBDownsample
getDownSampleRight() - Method in interface org.encog.util.downsample.Downsample
getDownSampleRight() - Method in class org.encog.util.downsample.RGBDownsample
getDownSampleTop() - Method in interface org.encog.util.downsample.Downsample
getDownSampleTop() - Method in class org.encog.util.downsample.RGBDownsample
getEGB() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
getElapsedMilliseconds() - Method in class org.encog.engine.util.Stopwatch
getElapsedTicks() - Method in class org.encog.engine.util.Stopwatch
getElapsedTime() - Method in interface org.encog.engine.network.train.gradient.FlatGradientWorker
getElapsedTime() - Method in class org.encog.engine.network.train.gradient.GradientWorkerCPU
getElements() - Method in class org.encog.bot.browse.range.DocumentRange
getEnabledDevices() - Method in class org.encog.engine.opencl.EncogCL
getEncodeLength() - Method in interface org.encog.engine.EngineNeuralNetwork
getEncodeLength() - Method in class org.encog.engine.network.flat.FlatNetwork
getEncogVersion() - Method in interface org.encog.persist.EncogCollection
getEncogVersion() - Method in class org.encog.persist.EncogMemoryCollection
getEncogVersion() - Method in class org.encog.persist.EncogPersistedCollection
getEnd() - Method in class org.encog.bot.browse.range.DocumentRange
getEndingIndex() - Method in class org.encog.normalize.segregate.index.IndexRangeSegregator
getEndingIndex() - Method in class org.encog.normalize.segregate.index.IndexSampleSegregator
getEndTraining() - Method in class org.encog.engine.network.flat.FlatNetwork
getEquilateral() - Method in class org.encog.normalize.output.nominal.OutputEquilateral
getError() - Method in class org.encog.engine.concurrency.calc.CalculationResult
getError() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getError() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp
getError() - Method in interface org.encog.engine.network.train.TrainFlatNetwork
getError() - Method in class org.encog.engine.opencl.kernels.KernelNetworkCalc
getError() - Method in class org.encog.neural.networks.training.BasicTraining: Get the current error percent from the training.
getError() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
getError() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper
getError() - Method in class org.encog.neural.networks.training.lma.JacobianChainRule
getError() - Method in class org.encog.neural.networks.training.neat.NEATTraining: return The error for the best genome.
getError() - Method in interface org.encog.neural.networks.training.Train: Get the current error percent from the training.
getErrors() - Method in class org.encog.engine.opencl.kernels.KernelNetworkCalc
getErrors() - Method in class org.encog.engine.opencl.kernels.KernelNetworkTrain
getExchange() - Method in class org.encog.neural.data.market.TickerSymbol
getF1Neurons() - Method in class org.encog.neural.networks.logic.BAMLogic
getF2Neurons() - Method in class org.encog.neural.networks.logic.BAMLogic
getFalseValue() - Method in class org.encog.normalize.output.nominal.OutputOneOf
getFc() - Method in class org.encog.neural.data.buffer.EncogEGBFile
getField() - Method in class org.encog.normalize.input.NeuralDataFieldHolder
getField() - Method in class org.encog.normalize.output.OutputFieldRangeMapped
getField() - Method in class org.encog.persist.persistors.generic.FieldMapping
getFile() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
getFile() - Method in class org.encog.neural.data.buffer.EncogEGBFile
getFile() - Method in class org.encog.normalize.input.InputFieldCSV
getFile() - Method in class org.encog.persist.location.FilePersistence
getFilename() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet
getFilename() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getFileVersion() - Method in interface org.encog.persist.EncogCollection
getFileVersion() - Method in class org.encog.persist.EncogMemoryCollection
getFileVersion() - Method in class org.encog.persist.EncogPersistedCollection
getFlat() - Method in class org.encog.engine.opencl.kernels.KernelNetworkCalc
getFlat() - Method in class org.encog.neural.networks.structure.NeuralStructure
getFlatContextIndex() - Method in class org.encog.neural.networks.layers.ContextLayer
getFlatTraining() - Method in class org.encog.neural.networks.training.propagation.Propagation
getFlatUpdate() - Method in class org.encog.neural.networks.structure.NeuralStructure
getFold() - Method in class org.encog.neural.networks.training.svm.SVMTrain
getFolded() - Method in class org.encog.neural.networks.training.cross.CrossTraining
getFormat() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet
getFrom() - Method in class org.encog.neural.networks.NeuralDataMapping
getFrom() - Method in class org.encog.util.time.TimeSpan
getFromLayer() - Method in class org.encog.neural.networks.synapse.BasicSynapse
getFromLayer() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getFromLayer() - Method in interface org.encog.neural.networks.synapse.Synapse
getFromNeuron() - Method in class org.encog.neural.networks.synapse.neat.NEATLink
getFromNeuronCount() - Method in class org.encog.neural.networks.synapse.BasicSynapse
getFromNeuronCount() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getFromNeuronCount() - Method in interface org.encog.neural.networks.synapse.Synapse
getFromNeuronID() - Method in class org.encog.neural.networks.training.neat.NEATInnovation
getFromNeuronID() - Method in class org.encog.neural.networks.training.neat.NEATLinkGene
getGammaBegin() - Method in class org.encog.neural.networks.training.svm.SVMTrain
getGammaEnd() - Method in class org.encog.neural.networks.training.svm.SVMTrain
getGammaStep() - Method in class org.encog.neural.networks.training.svm.SVMTrain
getGene(int) - Method in class org.encog.solve.genetic.genome.Chromosome: Get the specified gene.
getGenes() - Method in class org.encog.solve.genetic.genome.Chromosome: Used the get the entire gene list.
getGenetic() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm
getGeneticAlgorithm() - Method in class org.encog.solve.genetic.genome.BasicGenome
getGenomeID() - Method in class org.encog.solve.genetic.genome.BasicGenome
getGenomeID() - Method in interface org.encog.solve.genetic.genome.Genome
getGenomes() - Method in class org.encog.solve.genetic.population.BasicPopulation
getGenomes() - Method in interface org.encog.solve.genetic.population.Population
getGensNoImprovement() - Method in class org.encog.solve.genetic.species.BasicSpecies
getGensNoImprovement() - Method in interface org.encog.solve.genetic.species.Species
getGlobalMemorySize() - Method in class org.encog.engine.opencl.EncogCLDevice
getGlobalRatio() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getGlobalRatio() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
getGlobalWork() - Method in class org.encog.engine.opencl.kernels.EncogKernel
getGroup() - Method in class org.encog.normalize.output.OutputFieldGrouped
getGroupedFields() - Method in class org.encog.normalize.output.BasicOutputFieldGroup
getGroupedFields() - Method in interface org.encog.normalize.output.OutputFieldGroup
getGroups() - Method in class org.encog.normalize.DataNormalization
getH() - Method in class org.encog.mathutil.matrices.decomposition.QRDecomposition: Return the Householder vectors
getHeaderBuffer() - Method in class org.encog.neural.data.buffer.EncogEGBFile
getHeight() - Method in class org.encog.neural.data.image.ImageNeuralDataSet
getHeight() - Method in class org.encog.util.ImageSize
getHidden() - Method in class org.encog.neural.prune.PruneIncremental
getHidden1Size() - Method in class org.encog.neural.prune.PruneIncremental
getHidden2Size() - Method in class org.encog.neural.prune.PruneIncremental
getHigh() - Method in class org.encog.engine.network.activation.ActivationRamp
getHigh() - Method in class org.encog.engine.network.activation.ActivationStep
getHigh() - Method in class org.encog.engine.util.IntRange
getHigh() - Method in class org.encog.mathutil.NumericRange
getHigh() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
getHigh() - Method in class org.encog.neural.prune.PruneIncremental
getHigh() - Method in class org.encog.normalize.output.mapped.MappedRange
getHigh() - Method in class org.encog.normalize.output.nominal.NominalItem
getHigh() - Method in class org.encog.normalize.output.nominal.OutputEquilateral
getHigh() - Method in class org.encog.normalize.output.OutputFieldRangeMapped
getHigh() - Method in class org.encog.normalize.segregate.SegregationRange
getHighSequence() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getID() - Method in class org.encog.engine.concurrency.TaskGroup
getID() - Method in class org.encog.neural.networks.layers.BasicLayer
getID() - Method in interface org.encog.neural.networks.layers.Layer
getId() - Method in class org.encog.solve.genetic.genes.BasicGene
getId() - Method in interface org.encog.solve.genetic.genes.Gene: Get the ID of this gene, -1 for undefined.
getIdAttribute() - Method in class org.encog.bot.browse.range.DocumentRange
getIdeal() - Method in class org.encog.neural.data.basic.BasicNeuralDataPair: Get the expected results.
getIdeal() - Method in class org.encog.neural.data.buffer.codec.ArrayDataCODEC
getIdeal() - Method in interface org.encog.neural.data.NeuralDataPair
getIdealArray() - Method in class org.encog.engine.data.BasicEngineData: Get the expected results.
getIdealArray() - Method in interface org.encog.engine.data.EngineData
getIdealArray() - Method in class org.encog.neural.data.basic.BasicNeuralDataPair
getIdealCount() - Method in class org.encog.neural.data.buffer.EncogEGBFile
getIdealSize() - Method in class org.encog.engine.data.BasicEngineDataSet: Get the size of the ideal dataset.
getIdealSize() - Method in interface org.encog.engine.data.EngineDataSet
getIdealSize() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Get the size of the ideal dataset.
getIdealSize() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
getIdealSize() - Method in class org.encog.neural.data.buffer.codec.ArrayDataCODEC
getIdealSize() - Method in class org.encog.neural.data.buffer.codec.CSVDataCODEC
getIdealSize() - Method in interface org.encog.neural.data.buffer.codec.DataSetCODEC
getIdealSize() - Method in class org.encog.neural.data.buffer.codec.ExcelCODEC
getIdealSize() - Method in class org.encog.neural.data.buffer.codec.NeuralDataSetCODEC
getIdealSize() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet
getIdealSize() - Method in class org.encog.neural.data.folded.FoldedDataSet
getIdealSize() - Method in interface org.encog.neural.data.NeuralDataSet
getIdealSize() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
getIdealSize() - Method in class org.encog.neural.data.union.UnionNeuralDataSet
getIdealSize() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getIdealXML() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getImage() - Method in class org.encog.neural.data.image.ImageNeuralData
getImageHeight() - Method in interface org.encog.util.downsample.Downsample
getImageHeight() - Method in class org.encog.util.downsample.RGBDownsample
getImagEigenvalues() - Method in class org.encog.mathutil.matrices.decomposition.EigenvalueDecomposition: Return the imaginary parts of the eigenvalues.
getImageWidth() - Method in interface org.encog.util.downsample.Downsample
getImageWidth() - Method in class org.encog.util.downsample.RGBDownsample
getInboundLinks() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getIncrement() - Method in class org.encog.mathutil.LinearCongruentialGenerator
getIndex() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
getInitialUpdate() - Method in class org.encog.neural.networks.training.concurrent.jobs.RPROPJob
getInnovationId() - Method in class org.encog.solve.genetic.genes.BasicGene
getInnovationId() - Method in interface org.encog.solve.genetic.genes.Gene
getInnovationID() - Method in class org.encog.solve.genetic.innovation.BasicInnovation
getInnovationID() - Method in interface org.encog.solve.genetic.innovation.Innovation
getInnovations() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getInnovations() - Method in class org.encog.solve.genetic.innovation.BasicInnovationList
getInnovations() - Method in interface org.encog.solve.genetic.innovation.InnovationList
getInnovations() - Method in class org.encog.solve.genetic.population.BasicPopulation
getInnovations() - Method in interface org.encog.solve.genetic.population.Population
getInnovationType() - Method in class org.encog.neural.networks.training.neat.NEATInnovation
getInput() - Method in class org.encog.neural.data.basic.BasicNeuralDataPair: Get the input data.
getInput() - Method in class org.encog.neural.data.buffer.codec.ArrayDataCODEC
getInput() - Method in interface org.encog.neural.data.NeuralDataPair
getInputArray() - Method in class org.encog.engine.data.BasicEngineData: Get the input data.
getInputArray() - Method in interface org.encog.engine.data.EngineData
getInputArray() - Method in class org.encog.neural.data.basic.BasicNeuralDataPair
getInputCount() - Method in interface org.encog.engine.EngineMachineLearning
getInputCount() - Method in class org.encog.engine.network.flat.FlatNetwork
getInputCount() - Method in class org.encog.neural.data.buffer.EncogEGBFile
getInputCount() - Method in class org.encog.neural.networks.BasicNetwork
getInputCount() - Method in class org.encog.neural.networks.svm.SVMNetwork
getInputCount() - Method in class org.encog.neural.networks.training.neat.NEATGenome
getInputCount() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getInputField() - Method in class org.encog.normalize.output.nominal.NominalItem
getInputFields() - Method in class org.encog.normalize.DataNormalization
getInputLayer() - Method in class org.encog.neural.networks.training.cpn.FindCPN
getInputNeuronCount() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getInputNeuronCount() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
getInputNeurons() - Method in class org.encog.neural.pattern.SVMPattern
getInputSize() - Method in class org.encog.engine.data.BasicEngineDataSet: Get the size of the input dataset.
getInputSize() - Method in interface org.encog.engine.data.EngineDataSet
getInputSize() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Get the size of the input dataset.
getInputSize() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
getInputSize() - Method in class org.encog.neural.data.buffer.codec.ArrayDataCODEC
getInputSize() - Method in class org.encog.neural.data.buffer.codec.CSVDataCODEC
getInputSize() - Method in interface org.encog.neural.data.buffer.codec.DataSetCODEC
getInputSize() - Method in class org.encog.neural.data.buffer.codec.ExcelCODEC
getInputSize() - Method in class org.encog.neural.data.buffer.codec.NeuralDataSetCODEC
getInputSize() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet
getInputSize() - Method in class org.encog.neural.data.folded.FoldedDataSet
getInputSize() - Method in interface org.encog.neural.data.NeuralDataSet
getInputSize() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
getInputSize() - Method in class org.encog.neural.data.union.UnionNeuralDataSet
getInputSize() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getInputWindowSize() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getInputXML() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getInstance() - Static method in class org.encog.Encog: Get the instance to the singleton.
getInstance() - Static method in class org.encog.engine.concurrency.calc.ConcurrentCalculate
getInstance() - Static method in class org.encog.engine.concurrency.EngineConcurrency
getInstance() - Static method in class org.encog.engine.EncogEngine: Get the instance to the singleton.
getInstance() - Static method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
getInstance() - Static method in class org.encog.script.EncogScriptEngineFactory
getInstarLayer() - Method in class org.encog.neural.networks.training.cpn.FindCPN
getInstarSynapse() - Method in class org.encog.neural.networks.training.cpn.FindCPN
getInt(String) - Method in class org.encog.util.csv.ReadCSV: Obtain a column as an integer referenced by a string.
getInteger(String) - Method in class org.encog.neural.data.PropertyData: Get a property as an integer.
getItems() - Method in class org.encog.bot.rss.RSS
getIteration() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getIteration() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp
getIteration() - Method in interface org.encog.engine.network.train.TrainFlatNetwork
getIteration() - Method in class org.encog.neural.networks.training.BasicTraining
getIteration() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getIteration() - Method in interface org.encog.neural.networks.training.Train
getIterations() - Method in class org.encog.neural.prune.PruneIncremental
getIterationsPer() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
getIterator() - Method in class org.encog.normalize.input.NeuralDataFieldHolder
getJacobian() - Method in interface org.encog.neural.networks.training.lma.ComputeJacobian
getJacobian() - Method in class org.encog.neural.networks.training.lma.JacobianChainRule
getJobUnit() - Method in class org.encog.engine.concurrency.job.JobUnitContext
getKernel() - Method in class org.encog.engine.opencl.kernels.EncogKernel
getKernelGlobalWorkgroup() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getKernelLocalWorkgroup() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getKernelNumberOfCalls() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getKernelRemainder() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getKernelRemainderGlobal() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getKernelRemainderPer() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getKernelType() - Method in class org.encog.neural.networks.svm.SVMNetwork
getKernelWorkPerCall() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getL() - Method in class org.encog.mathutil.matrices.decomposition.CholeskyDecomposition: Return triangular factor.
getL() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition: Return lower triangular factor
getL() - Method in class org.encog.neural.networks.logic.ART1Logic
getL() - Method in class org.encog.neural.pattern.ART1Pattern
getLanguage() - Method in class org.encog.script.EncogScript
getLastDelta() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkBackPropagation
getLastDelta() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
getLastGradient() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getLastGradient() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp
getLayer(String) - Method in class org.encog.neural.networks.BasicNetwork: Get the layer specified by the tag.
getLayerCounts() - Method in class org.encog.engine.network.flat.FlatNetwork
getLayerFeedCounts() - Method in class org.encog.engine.network.flat.FlatNetwork
getLayerIndex() - Method in class org.encog.engine.network.flat.FlatNetwork
getLayerOutput() - Method in class org.encog.engine.network.flat.FlatNetwork
getLayers() - Method in class org.encog.neural.networks.structure.NeuralStructure
getLayerTags() - Method in class org.encog.neural.networks.BasicNetwork
getLeader() - Method in class org.encog.solve.genetic.species.BasicSpecies
getLeader() - Method in interface org.encog.solve.genetic.species.Species
getLearningRate() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkBackPropagation
getLearningRate() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkManhattan
getLearningRate() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getLearningRate() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
getLearningRate() - Method in class org.encog.neural.networks.training.concurrent.jobs.BPROPJob
getLearningRate() - Method in class org.encog.neural.networks.training.cpn.TrainInstar
getLearningRate() - Method in class org.encog.neural.networks.training.cpn.TrainOutstar
getLearningRate() - Method in class org.encog.neural.networks.training.hebbian.HebbianTraining
getLearningRate() - Method in interface org.encog.neural.networks.training.LearningRate
getLearningRate() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
getLearningRate() - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
getLearningRate() - Method in class org.encog.neural.networks.training.simple.TrainAdaline
getLearningType() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getLength() - Method in class org.encog.normalize.output.multiplicative.MultiplicativeGroup
getLength() - Method in class org.encog.normalize.output.zaxis.ZAxisGroup
getLink() - Method in class org.encog.bot.rss.RSSItem: Get the hyperlink.
getLinks() - Method in class org.encog.neural.networks.training.neat.NEATGenome
getLoader() - Method in class org.encog.neural.data.market.MarketNeuralDataSet
getLocalMemorySize() - Method in class org.encog.engine.opencl.EncogCLDevice
getLocalRatio() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getLocalRatio() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
getLocalWork() - Method in class org.encog.engine.opencl.kernels.EncogKernel
getLocation() - Method in interface org.encog.persist.EncogCollection
getLocation() - Method in class org.encog.persist.EncogMemoryCollection
getLocation() - Method in class org.encog.persist.EncogPersistedCollection
getLogic() - Method in class org.encog.neural.networks.BasicNetwork
getLow() - Method in class org.encog.engine.network.activation.ActivationRamp
getLow() - Method in class org.encog.engine.network.activation.ActivationStep
getLow() - Method in class org.encog.engine.util.IntRange
getLow() - Method in class org.encog.mathutil.NumericRange
getLow() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
getLow() - Method in class org.encog.neural.prune.PruneIncremental
getLow() - Method in class org.encog.normalize.output.mapped.MappedRange
getLow() - Method in class org.encog.normalize.output.nominal.NominalItem
getLow() - Method in class org.encog.normalize.output.nominal.OutputEquilateral
getLow() - Method in class org.encog.normalize.output.OutputFieldRangeMapped
getLow() - Method in class org.encog.normalize.segregate.SegregationRange
getLowSequence() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getManager() - Method in interface org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformer: Get the manager.
getManager() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU: Get the manager.
getMap() - Method in class org.encog.util.http.CookieUtility: Allows access to the name/value pair list of cookies.
getMatingPopulation() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Get the mating population.
getMatrix(int, int, int, int) - Method in class org.encog.mathutil.matrices.Matrix: Get a submatrix.
getMatrix(int, int, int[]) - Method in class org.encog.mathutil.matrices.Matrix: Get a submatrix.
getMatrix(int[], int, int) - Method in class org.encog.mathutil.matrices.Matrix: Get a submatrix.
getMatrix(int[], int[]) - Method in class org.encog.mathutil.matrices.Matrix: Get a submatrix.
getMatrix() - Method in class org.encog.neural.networks.synapse.DirectSynapse
getMatrix() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Get the weight matrix.
getMatrix() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
getMatrix() - Method in interface org.encog.neural.networks.synapse.Synapse: Get the weight matrix.
getMatrix() - Method in class org.encog.neural.networks.synapse.WeightedSynapse: Get the weight matrix.
getMatrix() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse
getMatrixSize() - Method in class org.encog.neural.networks.synapse.DirectSynapse
getMatrixSize() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Get the size of the matrix, or zero if one is not defined.
getMatrixSize() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
getMatrixSize() - Method in interface org.encog.neural.networks.synapse.Synapse: Get the size of the matrix, or zero if one is not defined.
getMatrixSize() - Method in class org.encog.neural.networks.synapse.WeightedSynapse: Get the size of the matrix, or zero if one is not defined.
getMatrixSize() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse
getMax() - Method in class org.encog.neural.prune.HiddenLayerParams
getMax() - Method in class org.encog.normalize.input.BasicInputField
getMax() - Method in interface org.encog.normalize.input.InputField
getMaxClockFrequency() - Method in class org.encog.engine.opencl.EncogCLDevice
getMaxComputeUnits() - Method in class org.encog.engine.opencl.EncogCLDevice
getMaxStep() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getMaxStep() - Method in class org.encog.neural.networks.training.concurrent.jobs.RPROPJob
getMaxWinners() - Method in class org.encog.engine.network.activation.ActivationCompetitive
getMaxWorkGroupSize() - Method in class org.encog.engine.opencl.EncogCLDevice
getMaxWorkGroupSize() - Method in class org.encog.engine.opencl.kernels.EncogKernel
getMean() - Method in class org.encog.mathutil.NumericRange
getMembers() - Method in class org.encog.solve.genetic.species.BasicSpecies
getMembers() - Method in interface org.encog.solve.genetic.species.Species
getMemoryScore() - Method in class org.encog.util.benchmark.EncogBenchmark
getMessage() - Method in class org.encog.cloud.CloudRequest
getMethod() - Method in class org.encog.bot.browse.range.Form
getMin() - Method in class org.encog.neural.prune.HiddenLayerParams
getMin() - Method in class org.encog.normalize.input.BasicInputField
getMin() - Method in interface org.encog.normalize.input.InputField
getMinutes() - Method in class org.encog.neural.networks.training.strategy.end.EndMinutesStrategy
getMinutesLeft() - Method in class org.encog.neural.networks.training.strategy.end.EndMinutesStrategy
getMode() - Static method in class org.encog.engine.util.ErrorCalculation: get the error calculation mode, this is static and therefore global to all Enocg training.
getModels() - Method in class org.encog.neural.networks.svm.SVMNetwork
getModulus() - Method in class org.encog.mathutil.LinearCongruentialGenerator
getMomentum() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkBackPropagation
getMomentum() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getMomentum() - Method in class org.encog.neural.networks.training.concurrent.jobs.BPROPJob
getMomentum() - Method in interface org.encog.neural.networks.training.Momentum
getMomentum() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
getMultiplier() - Method in class org.encog.mathutil.LinearCongruentialGenerator
getMultiplier() - Method in class org.encog.normalize.output.zaxis.ZAxisGroup
getMutate() - Method in class org.encog.solve.genetic.GeneticAlgorithm
getMutationPercent() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Get the mutation percent.
getName() - Method in class org.encog.bot.browse.range.FormElement
getName() - Method in class org.encog.engine.opencl.EncogCLItem
getName() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
getName() - Method in class org.encog.neural.networks.layers.BasicLayer
getName() - Method in interface org.encog.neural.networks.Network
getName() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getName() - Method in class org.encog.parse.tags.Tag
getName() - Method in class org.encog.persist.BasicPersistedObject
getName() - Method in class org.encog.persist.BasicPersistedSubObject: Not implemented.
getName() - Method in class org.encog.persist.DirectoryEntry
getName() - Method in interface org.encog.persist.EncogPersistedObject
getName() - Method in interface org.encog.script.IndividualEngineFactory
getName() - Method in class org.encog.solve.genetic.population.BasicPopulation
getNeatActivationFunction() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getNeighborhood() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
getNetwork() - Method in class org.encog.engine.concurrency.calc.ConcurrentCalculate
getNetwork() - Method in interface org.encog.engine.network.train.gradient.FlatGradientWorker
getNetwork() - Method in class org.encog.engine.network.train.gradient.GradientWorkerCPU
getNetwork() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getNetwork() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp
getNetwork() - Method in interface org.encog.engine.network.train.TrainFlatNetwork
getNetwork() - Method in class org.encog.neural.networks.layers.BasicLayer
getNetwork() - Method in interface org.encog.neural.networks.layers.Layer
getNetwork() - Method in class org.encog.neural.networks.logic.ARTLogic
getNetwork() - Method in class org.encog.neural.networks.logic.BAMLogic
getNetwork() - Method in class org.encog.neural.networks.logic.FeedforwardLogic
getNetwork() - Method in class org.encog.neural.networks.structure.NeuralStructure
getNetwork() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Get the best network from the training.
getNetwork() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
getNetwork() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
getNetwork() - Method in class org.encog.neural.networks.training.cpn.TrainInstar
getNetwork() - Method in class org.encog.neural.networks.training.cpn.TrainOutstar
getNetwork() - Method in class org.encog.neural.networks.training.cross.CrossTraining
getNetwork() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm
getNetwork() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper: Get the current best neural network.
getNetwork() - Method in class org.encog.neural.networks.training.hebbian.HebbianTraining
getNetwork() - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
getNetwork() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getNetwork() - Method in class org.encog.neural.networks.training.propagation.Propagation
getNetwork() - Method in class org.encog.neural.networks.training.simple.TrainAdaline
getNetwork() - Method in class org.encog.neural.networks.training.svd.SVDTraining
getNetwork() - Method in class org.encog.neural.networks.training.svm.SVMTrain
getNetwork() - Method in interface org.encog.neural.networks.training.Train: Get the current best network from the training.
getNetwork() - Method in class org.encog.neural.prune.PruneSelective
getNetworkDepth() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getNetworkDepth() - Method in class org.encog.neural.networks.training.neat.NEATGenome
getNetworkInputLayerSize() - Method in class org.encog.normalize.DataNormalization
getNetworkOutputLayerSize() - Method in class org.encog.normalize.DataNormalization
getNeuralDataSet() - Method in class org.encog.normalize.input.InputFieldNeuralDataSet
getNeuronCount() - Method in class org.encog.engine.network.flat.FlatNetwork
getNeuronCount() - Method in class org.encog.neural.networks.layers.BasicLayer: Get the neuron count for this layer.
getNeuronCount() - Method in interface org.encog.neural.networks.layers.Layer
getNeuronCount() - Method in class org.encog.neural.networks.logic.ThermalLogic
getNeuronID() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getNeuronID() - Method in class org.encog.neural.networks.training.neat.NEATInnovation
getNeurons() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getNeurons() - Method in class org.encog.neural.networks.training.neat.NEATGenome
getNeurons() - Method in class org.encog.neural.pattern.NEATPattern
getNeuronType() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getNeuronType() - Method in class org.encog.neural.networks.training.neat.NEATInnovation
getNeuronType() - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene
getNext() - Method in class org.encog.neural.networks.layers.BasicLayer
getNext() - Method in interface org.encog.neural.networks.layers.Layer: Get a list of all of the outbound synapse connections from this layer.
getNextID() - Method in class org.encog.neural.networks.structure.NeuralStructure: Get the next layer id.
getNextLayers() - Method in class org.encog.neural.networks.layers.BasicLayer
getNextLayers() - Method in interface org.encog.neural.networks.layers.Layer
getNormalization() - Method in class org.encog.normalize.segregate.index.IndexSegregator
getNormalization() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
getNormalization() - Method in class org.encog.normalize.segregate.RangeSegregator
getNormalization() - Method in interface org.encog.normalize.segregate.Segregator
getNoTasks() - Method in class org.encog.engine.concurrency.TaskGroup
getNumber() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
getNumberFormatter() - Method in class org.encog.util.csv.CSVFormat
getNumberOfRecords() - Method in class org.encog.neural.data.buffer.EncogEGBFile
getNumFolds() - Method in class org.encog.neural.data.folded.FoldedDataSet
getNumGenes() - Method in class org.encog.neural.networks.training.neat.NEATGenome
getNumThreads() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getNumThreads() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp
getNumThreads() - Method in interface org.encog.engine.network.train.TrainFlatNetwork
getNumThreads() - Method in class org.encog.neural.networks.training.propagation.Propagation
getNumToSpawn() - Method in class org.encog.solve.genetic.species.BasicSpecies
getNumToSpawn() - Method in interface org.encog.solve.genetic.species.Species
getOffset() - Method in class org.encog.normalize.input.InputFieldCSV
getOffset() - Method in class org.encog.normalize.input.InputFieldEncogCollection
getOffset() - Method in class org.encog.normalize.input.InputFieldNeuralDataSet
getOldAgePenalty() - Method in class org.encog.solve.genetic.population.BasicPopulation
getOldAgePenalty() - Method in interface org.encog.solve.genetic.population.Population
getOldAgeThreshold() - Method in class org.encog.solve.genetic.population.BasicPopulation
getOldAgeThreshold() - Method in interface org.encog.solve.genetic.population.Population
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationBiPolar: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationCompetitive: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in interface org.encog.engine.network.activation.ActivationFunction: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationGaussian: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationLinear: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationLOG: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationRamp: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationSigmoid: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationSIN: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationSoftMax: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationStep: Returns the OpenCL expression for this activation function.
getOpenCLExpression(boolean) - Method in class org.encog.engine.network.activation.ActivationTANH: Returns the OpenCL expression for this activation function.
getOrganism() - Method in class org.encog.solve.genetic.genome.BasicGenome
getOrganism() - Method in interface org.encog.solve.genetic.genome.Genome
getOriginal() - Method in class org.encog.bot.browse.Address
getOutput() - Method in class org.encog.neural.networks.NeuralOutputHolder
getOutput() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getOutput() - Method in class org.encog.neural.networks.training.cross.NetworkFold
getOutputActivationFunction() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getOutputboundLinks() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getOutputCount() - Method in interface org.encog.engine.EngineMachineLearning
getOutputCount() - Method in class org.encog.engine.network.flat.FlatNetwork
getOutputCount() - Method in class org.encog.neural.networks.BasicNetwork
getOutputCount() - Method in class org.encog.neural.networks.svm.SVMNetwork
getOutputCount() - Method in class org.encog.neural.networks.training.neat.NEATGenome
getOutputCount() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getOutputFieldCount() - Method in class org.encog.normalize.DataNormalization
getOutputFields() - Method in class org.encog.normalize.DataNormalization
getOutputNeuronCount() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getOutputNeuronCount() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
getOutputNeurons() - Method in class org.encog.neural.pattern.SVMPattern
getOutstarLayer() - Method in class org.encog.neural.networks.training.cpn.FindCPN
getOutstarSynapse() - Method in class org.encog.neural.networks.training.cpn.FindCPN
getOwner() - Method in class org.encog.bot.browse.range.FormElement
getOwner() - Method in class org.encog.engine.concurrency.job.JobUnitContext
getOwner() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
getOwner() - Method in class org.encog.neural.data.folded.FoldedDataSet
getPair() - Method in class org.encog.normalize.input.NeuralDataFieldHolder
getPairXML() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getParamActivationMutationRate() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamChanceAddLink() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamChanceAddNode() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamChanceAddRecurrentLink() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamCompatibilityThreshold() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamCrossoverRate() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamMaxActivationPerturbation() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamMaxNumberOfSpecies() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamMaxPermittedNeurons() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamMaxWeightPerturbation() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamMutationRate() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamNames() - Method in class org.encog.engine.network.activation.ActivationBiPolar
getParamNames() - Method in class org.encog.engine.network.activation.ActivationCompetitive
getParamNames() - Method in interface org.encog.engine.network.activation.ActivationFunction
getParamNames() - Method in class org.encog.engine.network.activation.ActivationGaussian
getParamNames() - Method in class org.encog.engine.network.activation.ActivationLinear
getParamNames() - Method in class org.encog.engine.network.activation.ActivationLOG
getParamNames() - Method in class org.encog.engine.network.activation.ActivationRamp
getParamNames() - Method in class org.encog.engine.network.activation.ActivationSigmoid
getParamNames() - Method in class org.encog.engine.network.activation.ActivationSIN
getParamNames() - Method in class org.encog.engine.network.activation.ActivationSoftMax
getParamNames() - Method in class org.encog.engine.network.activation.ActivationStep
getParamNames() - Method in class org.encog.engine.network.activation.ActivationTANH
getParamNumAddLinkAttempts() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamNumGensAllowedNoImprovement() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamNumTrysToFindLoopedLink() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamNumTrysToFindOldLink() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParamProbabilityWeightReplaced() - Method in class org.encog.neural.networks.training.neat.NEATTraining
getParams() - Method in class org.encog.cloud.AsynchronousCloudRequest
getParams() - Method in class org.encog.engine.network.activation.ActivationBiPolar
getParams() - Method in class org.encog.engine.network.activation.ActivationCompetitive
getParams() - Method in interface org.encog.engine.network.activation.ActivationFunction
getParams() - Method in class org.encog.engine.network.activation.ActivationGaussian
getParams() - Method in class org.encog.engine.network.activation.ActivationLinear
getParams() - Method in class org.encog.engine.network.activation.ActivationLOG
getParams() - Method in class org.encog.engine.network.activation.ActivationRamp
getParams() - Method in class org.encog.engine.network.activation.ActivationSigmoid
getParams() - Method in class org.encog.engine.network.activation.ActivationSIN
getParams() - Method in class org.encog.engine.network.activation.ActivationSoftMax
getParams() - Method in class org.encog.engine.network.activation.ActivationStep
getParams() - Method in class org.encog.engine.network.activation.ActivationTANH
getParams() - Method in class org.encog.neural.networks.svm.SVMNetwork
getParent() - Method in class org.encog.bot.browse.range.DocumentRange
getPattern() - Method in class org.encog.neural.prune.PruneIncremental
getPeak() - Method in interface org.encog.engine.network.rbf.RadialBasisFunction: Get the center of this RBD.
getPeak() - Method in class org.encog.mathutil.rbf.BasicRBF: Get the center of this RBD.
getPercentToMate() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Get the percent to mate.
getPivot() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition: Return pivot permutation vector
getPixelMap() - Method in interface org.encog.util.downsample.Downsample
getPixelMap() - Method in class org.encog.util.downsample.RGBDownsample
getPlatform() - Method in class org.encog.engine.opencl.EncogCLDevice
getPlatform() - Method in class org.encog.engine.opencl.EncogCLPlatform
getPlatform() - Method in interface org.encog.persist.EncogCollection
getPlatform() - Method in class org.encog.persist.EncogMemoryCollection
getPlatform() - Method in class org.encog.persist.EncogPersistedCollection
getPlatforms() - Method in class org.encog.engine.opencl.EncogCL
getPlatformString(int) - Method in class org.encog.engine.opencl.EncogCLPlatform: Get a config string from the platform.
getPoints() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getPopulation() - Method in class org.encog.solve.genetic.GeneticAlgorithm
getPopulation() - Method in class org.encog.solve.genetic.species.BasicSpecies
getPopulationSize() - Method in class org.encog.solve.genetic.population.BasicPopulation: Get the population size.
getPopulationSize() - Method in interface org.encog.solve.genetic.population.Population
getPosX() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getPosY() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getPredictWindowSize() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getPreviousLayers(Layer) - Method in class org.encog.neural.networks.structure.NeuralStructure: Get the previous layers from the specified layer.
getPreviousSynapses(Layer) - Method in class org.encog.neural.networks.structure.NeuralStructure: Get the previous synapses.
getProblem() - Method in class org.encog.neural.networks.training.svm.SVMTrain
getProfile() - Method in class org.encog.neural.networks.training.propagation.Propagation
getProgram() - Method in class org.encog.engine.opencl.kernels.EncogKernel
getProperties() - Method in class org.encog.Encog
getProperties() - Method in class org.encog.neural.networks.BasicNetwork
getPropertyDouble(String) - Method in class org.encog.neural.networks.BasicNetwork: Get the specified property as a double.
getPropertyLong(String) - Method in class org.encog.neural.networks.BasicNetwork: Get the specified property as a long.
getPropertyString(String) - Method in class org.encog.neural.networks.BasicNetwork: Get the specified property as a string.
getQ() - Method in class org.encog.mathutil.matrices.decomposition.QRDecomposition: Generate and return the (economy-sized) orthogonal factor
getQueue() - Method in class org.encog.engine.opencl.EncogCLDevice
getR() - Method in class org.encog.mathutil.matrices.decomposition.QRDecomposition: Return the upper triangular factor
getRadialBasisFunction() - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer
getRadius() - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodBubble
getRadius() - Method in interface org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodFunction
getRadius() - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodRBF
getRadius() - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingle: The radius for this neighborhood function is always 1.
getRadius() - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingleRBF
getRaf() - Method in class org.encog.neural.data.buffer.EncogEGBFile
getRandom() - Method in class org.encog.mathutil.randomize.BasicRandomizer
getRatioX() - Method in interface org.encog.util.downsample.Downsample
getRatioX() - Method in class org.encog.util.downsample.RGBDownsample
getRatioY() - Method in interface org.encog.util.downsample.Downsample
getRatioY() - Method in class org.encog.util.downsample.RGBDownsample
getRBF() - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodRBF
getRealEigenvalues() - Method in class org.encog.mathutil.matrices.decomposition.EigenvalueDecomposition: Return the real parts of the eigenvalues.
getRecord(long, EngineData) - Method in class org.encog.engine.data.BasicEngineDataSet: Get a record by index into the specified pair.
getRecord(long, EngineData) - Method in interface org.encog.engine.data.EngineIndexableSet: Read an individual record, specified by index, in random order.
getRecord(long, EngineData) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Get a record by index into the specified pair.
getRecord(long, EngineData) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Read an individual record.
getRecord(long, EngineData) - Method in class org.encog.neural.data.folded.FoldedDataSet: Read an individual record, specified by index, in random order.
getRecordBuffer() - Method in class org.encog.neural.data.buffer.EncogEGBFile
getRecordCount() - Method in class org.encog.engine.data.BasicEngineDataSet
getRecordCount() - Method in interface org.encog.engine.data.EngineIndexableSet: Determine the total number of records in the set.
getRecordCount() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
getRecordCount() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
getRecordCount() - Method in class org.encog.neural.data.buffer.EncogEGBFile
getRecordCount() - Method in class org.encog.neural.data.folded.FoldedDataSet: Determine the total number of records in the set.
getRecordCount() - Method in class org.encog.normalize.DataNormalization
getRecordSize() - Method in class org.encog.neural.data.buffer.EncogEGBFile
getRef() - Method in class org.encog.persist.persistors.generic.FieldMapping
getReference(Object) - Method in class org.encog.persist.persistors.generic.ObjectTagger: Get the reference for the specified object.
getReport() - Method in class org.encog.normalize.DataNormalization
getResourceName() - Method in class org.encog.normalize.input.InputFieldEncogCollection
getResourceName() - Method in class org.encog.normalize.target.NormalizationStorageEncogCollection
getResponseProperty(String) - Method in class org.encog.cloud.CloudRequest: Get a response property.
getResult() - Method in class org.encog.neural.networks.NeuralOutputHolder
getResults() - Method in class org.encog.neural.prune.PruneIncremental
getRms() - Method in class org.encog.mathutil.NumericRange
getRootLogger() - Static method in class org.encog.util.logging.Logging
getRow(int) - Method in class org.encog.mathutil.matrices.Matrix: Get the specified row as a sub-matrix.
getRowErrors() - Method in interface org.encog.neural.networks.training.lma.ComputeJacobian
getRowErrors() - Method in class org.encog.neural.networks.training.lma.JacobianChainRule
getRows() - Method in class org.encog.mathutil.matrices.Matrix: Get the number of rows in the matrix.
getRunCycles() - Method in class org.encog.neural.pattern.BoltzmannPattern
getRunningCounts() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
getS() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition: Return the diagonal matrix of singular values
getSamples() - Method in class org.encog.mathutil.NumericRange
getSampleSize() - Method in class org.encog.normalize.segregate.index.IndexSampleSegregator
getScore() - Method in class org.encog.solve.anneal.SimulatedAnnealing
getScore() - Method in class org.encog.solve.genetic.genome.BasicGenome
getScore() - Method in interface org.encog.solve.genetic.genome.Genome
getSeed() - Method in class org.encog.mathutil.LinearCongruentialGenerator
getSegmentationRatio() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
getSegmentationRatio() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
getSegregators() - Method in class org.encog.normalize.DataNormalization
getSeparator() - Method in class org.encog.util.csv.CSVFormat
getSequence() - Method in class org.encog.neural.data.temporal.TemporalPoint
getSequenceFromDate(Date) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Create a sequence number from a time.
getSequenceGrandularity() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getService() - Method in class org.encog.cloud.CloudRequest
getSession() - Method in class org.encog.cloud.CloudRequest
getSession() - Method in class org.encog.cloud.EncogCloud
getShouldStop() - Method in class org.encog.engine.concurrency.job.ConcurrentJob
getSingularValues() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition: Return the one-dimensional array of singular values
getSlope() - Method in class org.encog.engine.network.activation.ActivationLinear
getSource() - Method in class org.encog.bot.browse.range.DocumentRange
getSource() - Method in class org.encog.script.EncogScript
getSourceField() - Method in class org.encog.normalize.output.mapped.OutputFieldEncode
getSourceField() - Method in class org.encog.normalize.output.OutputFieldGrouped
getSourceField() - Method in class org.encog.normalize.segregate.RangeSegregator
getSourceName() - Method in class org.encog.engine.opencl.kernels.EncogKernel
getSpan(TimeUnit) - Method in class org.encog.util.time.TimeSpan: Get the time span specified by the unit.
getSpawnsRequired() - Method in class org.encog.solve.genetic.species.BasicSpecies
getSpawnsRequired() - Method in interface org.encog.solve.genetic.species.Species
getSpecies() - Method in class org.encog.solve.genetic.population.BasicPopulation
getSpecies() - Method in interface org.encog.solve.genetic.population.Population
getSpeciesID() - Method in class org.encog.neural.networks.training.neat.NEATGenome
getSpeciesID() - Method in class org.encog.solve.genetic.species.BasicSpecies
getSpeciesID() - Method in interface org.encog.solve.genetic.species.Species
getSplitX() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getSplitX() - Method in class org.encog.neural.networks.training.neat.NEATInnovation
getSplitX() - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene
getSplitY() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getSplitY(int) - Method in class org.encog.neural.networks.training.neat.NEATGenome: Get the specified split y.
getSplitY() - Method in class org.encog.neural.networks.training.neat.NEATInnovation
getSplitY() - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene
getStandardDeviation() - Method in class org.encog.mathutil.NumericRange
getStartingIndex() - Method in class org.encog.normalize.segregate.index.IndexRangeSegregator
getStartingIndex() - Method in class org.encog.normalize.segregate.index.IndexSampleSegregator
getStartingPoint() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getStartTemperature() - Method in class org.encog.solve.anneal.SimulatedAnnealing
getStatement() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
getStatus() - Method in class org.encog.cloud.CloudRequest
getStatus() - Method in class org.encog.neural.data.buffer.BinaryDataLoader
getStopTemperature() - Method in class org.encog.solve.anneal.SimulatedAnnealing
getStorage() - Method in class org.encog.normalize.DataNormalization
getStrategies() - Method in class org.encog.neural.networks.training.BasicTraining
getStrategies() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
getStrategies() - Method in class org.encog.neural.networks.training.neat.NEATTraining: Returns an empty list, strategies are not supported.
getStrategies() - Method in interface org.encog.neural.networks.training.Train
getStructure() - Method in class org.encog.neural.networks.BasicNetwork
getStructure() - Method in interface org.encog.neural.networks.Network
getSubfieldCount() - Method in class org.encog.normalize.output.mapped.OutputFieldEncode
getSubfieldCount() - Method in class org.encog.normalize.output.multiplicative.OutputFieldMultiplicative
getSubfieldCount() - Method in class org.encog.normalize.output.nominal.OutputEquilateral: This is the total number of nominal items minus 1.
getSubfieldCount() - Method in class org.encog.normalize.output.nominal.OutputOneOf
getSubfieldCount() - Method in interface org.encog.normalize.output.OutputField
getSubfieldCount() - Method in class org.encog.normalize.output.OutputFieldDirect
getSubfieldCount() - Method in class org.encog.normalize.output.OutputFieldRangeMapped
getSubfieldCount() - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxis
getSubfieldCount() - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxisSynthetic
getSubsets() - Method in class org.encog.neural.data.union.UnionNeuralDataSet
getSumActivation() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
getSurvivalRate() - Method in class org.encog.solve.genetic.population.BasicPopulation
getSurvivalRate() - Method in interface org.encog.solve.genetic.population.Population
getSvmType() - Method in class org.encog.neural.networks.svm.SVMNetwork
getSymbol() - Method in class org.encog.neural.data.market.TickerSymbol
getSynapses() - Method in class org.encog.neural.networks.structure.NeuralStructure
getTag() - Method in class org.encog.bot.dataunit.TagDataUnit
getTag() - Method in class org.encog.parse.tags.read.ReadTags: Return the last tag found, this is normally called just after the read function returns a zero.
getTags(Layer) - Method in class org.encog.neural.networks.BasicNetwork: Get a list of all of the tags on a specific layer.
getTarget() - Method in class org.encog.bot.browse.range.Link
getTarget() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
getTarget() - Method in class org.encog.persist.persistors.generic.FieldMapping
getTaskNumber() - Method in class org.encog.engine.concurrency.job.JobUnitContext
getTempDataArray() - Method in class org.encog.engine.opencl.kernels.KernelNetworkTrain
getTemperature() - Method in class org.encog.neural.networks.logic.BoltzmannLogic
getTemperature() - Method in class org.encog.neural.pattern.BoltzmannPattern
getTemperature() - Method in class org.encog.solve.anneal.SimulatedAnnealing
getText() - Method in class org.encog.bot.dataunit.TextDataUnit
getText() - Method in class org.encog.neural.data.TextData
getTextOnly() - Method in class org.encog.bot.browse.range.DocumentRange: Get the text from this range.
getThermalLayer() - Method in class org.encog.neural.networks.logic.ThermalLogic
getThermalSynapse() - Method in class org.encog.neural.networks.logic.ThermalLogic
getThreadCount() - Method in class org.encog.engine.concurrency.DetermineWorkload
getThresholdHigh() - Method in class org.encog.engine.network.activation.ActivationRamp
getThresholdLow() - Method in class org.encog.engine.network.activation.ActivationRamp
getTicker() - Method in class org.encog.neural.data.market.loader.LoadedMarketData
getTicker() - Method in class org.encog.neural.data.market.MarketDataDescription
getTitle() - Method in class org.encog.bot.browse.WebPage: Get the title for this document.
getTitle() - Method in class org.encog.bot.rss.RSSItem: Get the item title.
getTo() - Method in class org.encog.neural.networks.NeuralDataMapping
getTo() - Method in class org.encog.util.time.TimeSpan
getToLayer() - Method in class org.encog.neural.networks.synapse.BasicSynapse
getToLayer() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getToLayer() - Method in interface org.encog.neural.networks.synapse.Synapse
getToNeuron() - Method in class org.encog.neural.networks.synapse.neat.NEATLink
getToNeuronCount() - Method in class org.encog.neural.networks.synapse.BasicSynapse
getToNeuronCount() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getToNeuronCount() - Method in interface org.encog.neural.networks.synapse.Synapse
getToNeuronID() - Method in class org.encog.neural.networks.training.neat.NEATInnovation
getToNeuronID() - Method in class org.encog.neural.networks.training.neat.NEATLinkGene
getTopErrors() - Method in class org.encog.neural.prune.PruneIncremental
getTopNetworks() - Method in class org.encog.neural.prune.PruneIncremental
getTotalConnections() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
getTotalCount() - Method in class org.encog.engine.network.flat.FlatLayer
getTrain() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
getTraining() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getTraining() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp
getTraining() - Method in interface org.encog.engine.network.train.TrainFlatNetwork
getTraining() - Method in class org.encog.engine.opencl.kernels.KernelNetworkCalc
getTraining() - Method in class org.encog.neural.networks.training.BasicTraining
getTraining() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
getTraining() - Method in class org.encog.neural.networks.training.hebbian.HebbianTraining
getTraining() - Method in class org.encog.neural.networks.training.neat.NEATTraining: Returns null, does not use a training set, rather uses a score function.
getTraining() - Method in interface org.encog.neural.networks.training.Train
getTraining() - Method in class org.encog.neural.prune.PruneIncremental
getTrainingData() - Method in class org.encog.engine.concurrency.calc.ConcurrentCalculate
getTrueValue() - Method in class org.encog.normalize.output.nominal.OutputOneOf
getType() - Method in class org.encog.bot.browse.range.Input
getType() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
getType() - Method in class org.encog.neural.networks.synapse.DirectSynapse
getType() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
getType() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
getType() - Method in interface org.encog.neural.networks.synapse.Synapse
getType() - Method in class org.encog.neural.networks.synapse.WeightedSynapse
getType() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse
getType() - Method in class org.encog.parse.tags.Tag
getType() - Method in class org.encog.persist.DirectoryEntry
getU() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition: Return upper triangular factor
getU() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition: Return the left singular vectors
getUnderlying() - Method in class org.encog.neural.data.folded.FoldedDataSet
getUpdateValues() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL
getUpdateValues() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkResilient
getUrl() - Method in class org.encog.bot.browse.Address
getUrl() - Method in class org.encog.cloud.AsynchronousCloudRequest
getUsedForNetworkInput() - Method in class org.encog.normalize.input.BasicInputField
getUsedForNetworkInput() - Method in interface org.encog.normalize.input.InputField
getV() - Method in class org.encog.mathutil.matrices.decomposition.EigenvalueDecomposition: Return the eigenvector matrix.
getV() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition: Return the right singular vectors
getValue() - Method in class org.encog.bot.browse.range.FormElement
getValue(int) - Method in class org.encog.normalize.input.BasicInputField: Not supported for this sort of class, may be implemented in subclasses.
getValue(int) - Method in interface org.encog.normalize.input.InputField: Called for input field types that require an index to get the current value.
getValue(int) - Method in class org.encog.normalize.input.InputFieldArray1D: Get the value from the specified index.
getValue(int) - Method in class org.encog.normalize.input.InputFieldArray2D: Read a value from the specified index.
getValue() - Method in class org.encog.normalize.output.mapped.MappedRange
getValue() - Method in class org.encog.solve.genetic.genes.CharGene
getValue() - Method in class org.encog.solve.genetic.genes.DoubleGene
getValue() - Method in class org.encog.solve.genetic.genes.IntegerGene
getValueXML() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getVender() - Method in class org.encog.engine.opencl.EncogCLItem
getVigilance() - Method in class org.encog.neural.networks.logic.ART1Logic
getVigilance() - Method in class org.encog.neural.pattern.ART1Pattern
getWeight() - Method in class org.encog.neural.networks.synapse.neat.NEATLink
getWeight() - Method in class org.encog.neural.networks.training.neat.NEATLinkGene
getWeightIndex() - Method in class org.encog.engine.network.flat.FlatNetwork
getWeightMatrixSize() - Method in class org.encog.neural.networks.BasicNetwork
getWeightMatrixSize() - Method in interface org.encog.neural.networks.Network
getWeightOutArray() - Method in class org.encog.engine.opencl.kernels.KernelNetworkTrain
getWeights() - Method in class org.encog.engine.network.flat.FlatNetwork
getWeights() - Method in interface org.encog.engine.network.train.gradient.FlatGradientWorker
getWeights() - Method in class org.encog.engine.network.train.gradient.GradientWorkerCPU
getWeights() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
getWeights() - Method in class org.encog.neural.networks.training.cross.NetworkFold
getWeightsAndBias() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
getWeightValues() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
getWhen() - Method in class org.encog.neural.data.market.loader.LoadedMarketData
getWhen() - Method in class org.encog.neural.data.market.MarketPoint
getWidth() - Method in interface org.encog.engine.network.rbf.RadialBasisFunction
getWidth() - Method in class org.encog.mathutil.rbf.BasicRBF
getWidth() - Method in class org.encog.neural.data.image.ImageNeuralDataSet
getWidth() - Method in class org.encog.util.ImageSize
getWinner() - Method in class org.encog.neural.networks.logic.ART1Logic
getWorkGroupLong(int) - Method in class org.encog.engine.opencl.kernels.EncogKernel: Get a long param from the device.
getWorstDistance() - Method in class org.encog.neural.networks.training.competitive.BestMatchingUnit
getX() - Method in class org.encog.neural.networks.layers.BasicLayer
getX() - Method in interface org.encog.neural.networks.layers.Layer
getXMLInput() - Method in class org.encog.persist.PersistReader
getXMLText(Node) - Static method in class org.encog.bot.rss.RSS: Simple utility method that obtains the text of an XML node.
getY() - Method in class org.encog.neural.networks.layers.BasicLayer
getY() - Method in interface org.encog.neural.networks.layers.Layer
getYoungBonusAgeThreshold() - Method in class org.encog.solve.genetic.population.BasicPopulation
getYoungBonusAgeThreshold() - Method in interface org.encog.solve.genetic.population.Population
getYoungScoreBonus() - Method in class org.encog.solve.genetic.population.BasicPopulation
getYoungScoreBonus() - Method in interface org.encog.solve.genetic.population.Population
gradients - Variable in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: The gradients.
GradientWorkerCPU - Class in org.encog.engine.network.train.gradient: Worker class for the mulithreaded training of flat networks.
GradientWorkerCPU(FlatNetwork, TrainFlatNetworkProp, EngineIndexableSet, int, int) - Constructor for class org.encog.engine.network.train.gradient.GradientWorkerCPU: Construct a gradient worker.
Greedy - Class in org.encog.neural.networks.training.strategy: A simple greedy strategy.
Greedy() - Constructor for class org.encog.neural.networks.training.strategy.Greedy

H

handleItem(ReadXML) - Method in class org.encog.persist.persistors.TrainingContinuationPersistor: Handle an item.
handleItems(ReadXML) - Method in class org.encog.persist.persistors.TrainingContinuationPersistor: Handle loading the items.
hasBias() - Method in class org.encog.neural.networks.layers.BasicLayer
hasBias() - Method in interface org.encog.neural.networks.layers.Layer
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationBiPolar
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationCompetitive
hasDerivative() - Method in interface org.encog.engine.network.activation.ActivationFunction
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationGaussian
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationLinear
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationLOG
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationRamp
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationSigmoid
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationSIN
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationSoftMax
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationStep
hasDerivative() - Method in class org.encog.engine.network.activation.ActivationTANH
HasFixedLength - Interface in org.encog.normalize.input: Is this input field of a fixed length, such as an array? Or is it read "iterator style" where we call "next" until there is no more data.
hashCode() - Method in class org.encog.mathutil.matrices.Matrix: Compute a hash code for this matrix.
hashCode() - Method in class org.encog.neural.data.market.TickerSymbol
hashCode() - Method in class org.encog.neural.networks.BasicNetwork: Generate a hash code.
hashCode() - Method in interface org.encog.neural.networks.Network: Generate a hash code.
hashCode() - Method in class org.encog.persist.DirectoryEntry
hashCode() - Method in class org.encog.solve.genetic.genes.IntegerGene
hasNext() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet.BasicNeuralIterator: Is there more data for the iterator to read?
hasNext() - Method in class org.encog.neural.data.buffer.BufferedDataSetIterator
hasNext() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet.CSVNeuralIterator: Determine if there is more data to be read.
hasNext() - Method in class org.encog.neural.data.folded.FoldedIterator
hasNext() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet.SQLNeuralIterator: Returns true if there is more data to be read.
hasNext() - Method in class org.encog.neural.data.union.UnionNeuralDataSet.UnionIterator: Determine if there is more data to be read from this iterator.
hasNext() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet.XMLNeuralIterator: Is there any more data to read?
hasReference(Object) - Method in class org.encog.persist.persistors.generic.ObjectTagger: Returns true if the object has a reference.
hasSameActivationFunction() - Method in class org.encog.engine.network.flat.FlatNetwork: Neural networks with only one type of activation function offer certain optimization options.
hasWinner() - Method in class org.encog.neural.networks.logic.ART1Logic
HEADER_SIZE - Static variable in class org.encog.neural.data.buffer.EncogEGBFile: The size of the file header.
HebbianTraining - Class in org.encog.neural.networks.training.hebbian: This class implements Hebbian learning for Enocg.
HebbianTraining(BasicNetwork, NeuralDataSet, boolean, double) - Constructor for class org.encog.neural.networks.training.hebbian.HebbianTraining: Construct a Hebbian training object.
HiddenLayerParams - Class in org.encog.neural.prune: Specifies the minimum and maximum neuron counts for a layer.
HiddenLayerParams(int, int) - Constructor for class org.encog.neural.prune.HiddenLayerParams: Construct a hidden layer param object with the specified min and max values.
HopfieldLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for an Hopfield type network.
HopfieldLogic() - Constructor for class org.encog.neural.networks.logic.HopfieldLogic
HopfieldPattern - Class in org.encog.neural.pattern: Create a Hopfield pattern.
HopfieldPattern() - Constructor for class org.encog.neural.pattern.HopfieldPattern
HOURS_DAY - Static variable in class org.encog.util.time.TimeSpan: Hours in a day.
HybridStrategy - Class in org.encog.neural.networks.training.strategy: A hybrid stragey allows a secondary training algorithm to be used.
HybridStrategy(Train) - Constructor for class org.encog.neural.networks.training.strategy.HybridStrategy: Construct a hybrid strategy with the default minimum improvement and toleration cycles.
HybridStrategy(Train, double, int, int) - Constructor for class org.encog.neural.networks.training.strategy.HybridStrategy: Create a hybrid strategy.
hypot(double, double) - Static method in class org.encog.mathutil.EncogMath: sqrt(a^2 + b^2) without under/overflow.

I

identity(int) - Static method in class org.encog.mathutil.matrices.MatrixMath: Return an identity matrix of the specified size.
ImageNeuralData - Class in org.encog.neural.data.image: An extension of the BasicNeuralData class that is designed to hold images for input into a neural network.
ImageNeuralData(Image) - Constructor for class org.encog.neural.data.image.ImageNeuralData: Construct an object based on an image.
ImageNeuralDataSet - Class in org.encog.neural.data.image: Store a collection of images for training with a neural network.
ImageNeuralDataSet(Downsample, boolean, double, double) - Constructor for class org.encog.neural.data.image.ImageNeuralDataSet: Construct this class with the specified downsampler.
ImageSize - Class in org.encog.util: Simple class to determine the size of an image.
ImageSize(Image) - Constructor for class org.encog.util.ImageSize: Determine the size of an image.
imageUpdate(Image, int, int, int, int, int) - Method in class org.encog.util.ImageSize: The image has been updated.
INC_Y - Static variable in class org.encog.neural.pattern.PatternConst: How much to increase y by as the network grows.
INDENT_X - Static variable in class org.encog.neural.pattern.PatternConst: How much to indent on the x-axis.
index - Variable in class org.encog.mathutil.libsvm.svm_node
INDEX_DOUBLE_CLOSE - Variable in class org.encog.neural.data.market.loader.LoadedMarketData
INDEX_DOUBLE_HIGH - Variable in class org.encog.neural.data.market.loader.LoadedMarketData
INDEX_DOUBLE_LOW - Variable in class org.encog.neural.data.market.loader.LoadedMarketData
INDEX_DOUBLE_OPEN - Variable in class org.encog.neural.data.market.loader.LoadedMarketData
INDEX_FILE - Static variable in class org.encog.util.http.URLUtility: The name of the usual default document.
Indexable - Interface in org.encog.neural.data: Specifies that a data set can be accessed in random order via an index.
IndexRangeSegregator - Class in org.encog.normalize.segregate.index: An index segregator is used to segregate the data according to its index.
IndexRangeSegregator() - Constructor for class org.encog.normalize.segregate.index.IndexRangeSegregator: Default constructor for reflection.
IndexRangeSegregator(int, int) - Constructor for class org.encog.normalize.segregate.index.IndexRangeSegregator: Construct an index range segregator.
IndexSampleSegregator - Class in org.encog.normalize.segregate.index: An index segregator is used to segregate the data according to its index.
IndexSampleSegregator() - Constructor for class org.encog.normalize.segregate.index.IndexSampleSegregator: The default constructor, for reflection.
IndexSampleSegregator(int, int, int) - Constructor for class org.encog.normalize.segregate.index.IndexSampleSegregator: Construct an index sample segregator.
IndexSegregator - Class in org.encog.normalize.segregate.index: The index segregator.
IndexSegregator() - Constructor for class org.encog.normalize.segregate.index.IndexSegregator
IndividualEngineFactory - Interface in org.encog.script
init(String) - Method in class org.encog.cloud.CloudTask: Setup this task.
init(FlatLayer[]) - Method in class org.encog.engine.network.flat.FlatNetwork: Construct a flat network.
init(OpenCLTrainingProfile) - Method in class org.encog.engine.opencl.kernels.KernelNetworkTrain: Setup the kernel.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.ART1Logic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.ARTLogic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.BAMLogic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.FeedforwardLogic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in interface org.encog.neural.networks.logic.NeuralLogic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.ThermalLogic: Setup the network logic, read parameters from the network.
init(Train) - Method in class org.encog.neural.networks.training.strategy.end.EndIterationsStrategy: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.end.EndMaxErrorStrategy: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.end.EndMinutesStrategy: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.Greedy: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.HybridStrategy: Initialize this strategy.
init(Train) - Method in interface org.encog.neural.networks.training.Strategy: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.RequiredImprovementStrategy: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.ResetStrategy: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.SmartLearningRate: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.SmartMomentum: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.StopTrainingStrategy: Initialize this strategy.
init() - Method in class org.encog.neural.prune.PruneIncremental: Init for prune.
init(DataNormalization) - Method in class org.encog.normalize.segregate.index.IndexSegregator: Setup this class with the specified normalization object.
init(DataNormalization) - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator: Init the segregator with the owning normalization object.
init(DataNormalization) - Method in class org.encog.normalize.segregate.RangeSegregator: Init the object.
init(DataNormalization) - Method in interface org.encog.normalize.segregate.Segregator: Setup this object to use the specified normalization object.
initCL() - Method in class org.encog.Encog: Enable OpenCL processing.
initCL() - Method in class org.encog.engine.concurrency.calc.ConcurrentCalculate: Init for OpenCL.
initCL() - Method in class org.encog.engine.EncogEngine: Enable OpenCL processing.
initForOutput() - Method in class org.encog.normalize.DataNormalization: Setup the row for output.
initForPass() - Method in class org.encog.normalize.DataNormalization: Setup the row for output.
INITIAL_DEPTH - Static variable in class org.encog.parse.PeekableInputStream: The depth to peek.
Innovation - Interface in org.encog.solve.genetic.innovation: Provides the interface for an innovation.
InnovationList - Interface in org.encog.solve.genetic.innovation: Defines a list of innovations.
Input - Class in org.encog.bot.browse.range: A form element that represents for input for text.
Input(WebPage) - Constructor for class org.encog.bot.browse.range.Input: Construct this Input element.
input(String) - Method in interface org.encog.script.ConsoleInputOutput
input(String) - Method in class org.encog.script.StandardConsole
InputField - Interface in org.encog.normalize.input: A Normalization input field.
InputFieldArray1D - Class in org.encog.normalize.input: An input field that comes from a 1D array.
InputFieldArray1D(boolean, double[]) - Constructor for class org.encog.normalize.input.InputFieldArray1D: Construct the 1D array field.
InputFieldArray2D - Class in org.encog.normalize.input: An input field that comes from a 2D array.
InputFieldArray2D(boolean, double[][], int) - Constructor for class org.encog.normalize.input.InputFieldArray2D: Construct a 2D array input field.
InputFieldCSV - Class in org.encog.normalize.input: An input field based on a CSV file.
InputFieldCSV() - Constructor for class org.encog.normalize.input.InputFieldCSV: Construct an InputFieldCSV with the default constructor.
InputFieldCSV(boolean, File, int) - Constructor for class org.encog.normalize.input.InputFieldCSV: Construct a input field for a CSV file.
InputFieldEncogCollection - Class in org.encog.normalize.input
InputFieldEncogCollection() - Constructor for class org.encog.normalize.input.InputFieldEncogCollection
InputFieldEncogCollection(String, int) - Constructor for class org.encog.normalize.input.InputFieldEncogCollection
InputFieldNeuralDataSet - Class in org.encog.normalize.input: An input field based on an Encog NeuralDataSet.
InputFieldNeuralDataSet(boolean, NeuralDataSet, int) - Constructor for class org.encog.normalize.input.InputFieldNeuralDataSet: Construct a input field based on a NeuralDataSet.
InputStreamPersistence - Class in org.encog.persist.location: This class allows Encog persistence to use a location that is based on an InputStream.
InputStreamPersistence(InputStream) - Constructor for class org.encog.persist.location.InputStreamPersistence: Construct this location.
inRange(double) - Method in class org.encog.normalize.output.mapped.MappedRange: Determine if the specified value is in the range.
inRange(double) - Method in class org.encog.normalize.segregate.SegregationRange: Is this value within the range.
IntegerBalanceSegregator - Class in org.encog.normalize.segregate: Balance based on an input value.
IntegerBalanceSegregator(InputField, int) - Constructor for class org.encog.normalize.segregate.IntegerBalanceSegregator: Construct an integer balance segregator.
IntegerBalanceSegregator() - Constructor for class org.encog.normalize.segregate.IntegerBalanceSegregator: Default constructor.
IntegerGene - Class in org.encog.solve.genetic.genes: A gene that contains an integer value.
IntegerGene() - Constructor for class org.encog.solve.genetic.genes.IntegerGene
IntRange - Class in org.encog.engine.util: A range of integers.
IntRange(int, int) - Constructor for class org.encog.engine.util.IntRange: Construct an integer range.
inverse() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition: Solves a set of equation systems of type A * X = B.
inverse() - Method in class org.encog.mathutil.matrices.Matrix
InverseMultiquadricFunction - Class in org.encog.mathutil.rbf: Multi-dimensional Inverse Multiquadric function.
InverseMultiquadricFunction(double, double, double) - Constructor for class org.encog.mathutil.rbf.InverseMultiquadricFunction: Construct a single-dimension Inverse-Multiquadric function with the specified peak, centers and widths.
InverseMultiquadricFunction(double, double[], double) - Constructor for class org.encog.mathutil.rbf.InverseMultiquadricFunction: Construct a multi-dimension Inverse-Multiquadric function with the specified peak, centers and widths.
InverseMultiquadricFunction(int) - Constructor for class org.encog.mathutil.rbf.InverseMultiquadricFunction: Create centered at zero, width 0, and peak 0.
is(String, boolean) - Method in class org.encog.parse.tags.read.ReadTags: Checks to see if the next tag is the tag specified.
isAutoSend() - Method in class org.encog.bot.browse.range.FormElement
isAutoSend() - Method in class org.encog.bot.browse.range.Input
isBetterThan(double, double) - Method in class org.encog.solve.genetic.genome.GenomeComparator: Determine if one score is better than the other.
isBias() - Method in class org.encog.engine.network.flat.FlatLayer
isCloseConnection() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
isConnected() - Method in class org.encog.cloud.EncogCloud
isConnected(Synapse, int, int) - Method in class org.encog.neural.networks.BasicNetwork: Determine if the specified connection is enabled.
isConnectedTo(Layer) - Method in class org.encog.neural.networks.layers.BasicLayer: Determine if this layer is connected to another layer.
isConnectedTo(Layer) - Method in interface org.encog.neural.networks.layers.Layer: Determine if this layer is connected to another.
isConnectionLimited() - Method in class org.encog.neural.networks.structure.NeuralStructure
isCPU() - Method in class org.encog.engine.opencl.EncogCLDevice
isDefined(String) - Method in class org.encog.neural.data.PropertyData: Determine of the specified property is defined.
isDuplicateLink(long, long) - Method in class org.encog.neural.networks.training.neat.NEATGenome: Determine if this is a duplicate link.
isEnabled() - Method in class org.encog.engine.opencl.EncogCLItem
isEnabled() - Method in class org.encog.solve.genetic.genes.BasicGene
isEnabled() - Method in interface org.encog.solve.genetic.genes.Gene
isExecuted() - Method in class org.encog.engine.concurrency.calc.CalculationResult
isForceWinner() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
isFullRank() - Method in class org.encog.mathutil.matrices.decomposition.QRDecomposition: Is the matrix full rank?
isIdeal() - Method in class org.encog.normalize.output.BasicOutputField
isIdeal() - Method in interface org.encog.normalize.output.OutputField
isIncluded() - Method in class org.encog.normalize.segregate.SegregationRange
isInput() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
isInRange() - Method in class org.encog.normalize.output.nominal.NominalItem
isInstanceOf(Class<?>, Class<?>) - Static method in class org.encog.util.obj.ReflectionUtil: Determine if one class is an instance of the other class.
isLimited() - Method in class org.encog.engine.network.flat.FlatNetwork
isLoadToMemory() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
isNonsingular() - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition: Is the matrix nonsingular?
isOja() - Method in class org.encog.neural.networks.training.hebbian.HebbianTraining
isPointInRange(TemporalPoint) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Is the specified point within the range.
isPredict() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
isPrimitive(Object) - Static method in class org.encog.util.obj.ReflectionUtil: Determine if the specified object is a primitive.
isRecurrent() - Method in class org.encog.neural.networks.structure.NeuralStructure
isRecurrent() - Method in class org.encog.neural.networks.synapse.neat.NEATLink
isRecurrent() - Method in class org.encog.neural.networks.training.neat.NEATLinkGene
isRecurrent() - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene
isRegression() - Method in class org.encog.neural.pattern.SVMPattern
isSelfConnected() - Method in class org.encog.neural.networks.layers.BasicLayer
isSelfConnected() - Method in class org.encog.neural.networks.synapse.BasicSynapse
isSelfConnected() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
isSelfConnected() - Method in interface org.encog.neural.networks.synapse.Synapse
isShouldMinimize() - Method in class org.encog.solve.anneal.SimulatedAnnealing
isSimple(Object) - Static method in class org.encog.util.obj.ReflectionUtil: Determine if an object is "simple", that is it should be persisted just with a .tostring.
isSingleThreaded() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
isSnapshot() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
isSnapshot() - Method in class org.encog.neural.networks.training.neat.NEATTraining
isSnapshot() - Method in class org.encog.neural.pattern.NEATPattern
isSPD() - Method in class org.encog.mathutil.matrices.decomposition.CholeskyDecomposition: Is the matrix symmetric and positive definite?
isSuccessful() - Method in class org.encog.engine.concurrency.calc.CalculationResult
isSupervised() - Method in class org.encog.engine.data.BasicEngineData: Determine if this data pair is supervised.
isSupervised() - Method in class org.encog.engine.data.BasicEngineDataSet: Determine if this neural data set is supervied.
isSupervised() - Method in interface org.encog.engine.data.EngineData
isSupervised() - Method in interface org.encog.engine.data.EngineDataSet
isSupervised() - Method in class org.encog.neural.data.basic.BasicNeuralDataPair: Determine if this data pair is supervised.
isSupervised() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Determine if this neural data set is supervied.
isSupervised() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
isSupervised() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet
isSupervised() - Method in class org.encog.neural.data.folded.FoldedDataSet
isSupervised() - Method in interface org.encog.neural.data.NeuralDataPair
isSupervised() - Method in interface org.encog.neural.data.NeuralDataSet
isSupervised() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
isSupervised() - Method in class org.encog.neural.data.union.UnionNeuralDataSet
isSupervised() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
isSupervised() - Method in class org.encog.neural.networks.training.hebbian.HebbianTraining
isTeachable() - Method in class org.encog.neural.networks.synapse.DirectSynapse
isTeachable() - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
isTeachable() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
isTeachable() - Method in interface org.encog.neural.networks.synapse.Synapse
isTeachable() - Method in class org.encog.neural.networks.synapse.WeightedSynapse
isTeachable() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse
isTrainingDone() - Method in class org.encog.neural.networks.training.BasicTraining
isTrainingDone() - Method in class org.encog.neural.networks.training.neat.NEATTraining
isTrainingDone() - Method in class org.encog.neural.networks.training.svm.SVMTrain
isTrainingDone() - Method in interface org.encog.neural.networks.training.Train
isUseBayesianRegularization() - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining
isUseOpenCL() - Method in class org.encog.engine.concurrency.calc.ConcurrentCalculate
isValid(EngineMachineLearning) - Method in class org.encog.engine.network.flat.ValidateForOpenCL: Determine if the network is valid for OpenCL.
isValid(EngineMachineLearning) - Method in interface org.encog.engine.validate.ValidateMachineLearning: Determine if the network is valid.
isValid(EngineMachineLearning) - Method in class org.encog.neural.networks.structure.ValidateForFlat: Determine if the specified neural network can be flat.
isValidResume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation: Determine if the specified continuation object is valid to resume with.
isValidResume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.Propagation: Determine if this specified training continuation object is valid for this training method.
isValidResume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Determine if the specified continuation object is valid to resume with.
isVector() - Method in class org.encog.mathutil.matrices.Matrix: Determine if the matrix is a vector.
isZero() - Method in class org.encog.mathutil.matrices.Matrix: Return true if every value in the matrix is zero.
iteration() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Perform one training iteration.
iteration(int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Perform one training iteration.
iteration() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Perform one training iteration.
iteration(int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Perform the specified number of training iterations.
iteration() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkSCG: Perform one iteration.
iteration() - Method in interface org.encog.engine.network.train.TrainFlatNetwork: Perform one training iteration.
iteration(int) - Method in interface org.encog.engine.network.train.TrainFlatNetwork: Perform one training iteration.
iteration() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Perform one iteration of simulated annealing.
iteration(int) - Method in class org.encog.neural.networks.training.BasicTraining: Perform the specified number of training iterations.
iteration() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Perform one training iteration.
iteration() - Method in class org.encog.neural.networks.training.cpn.TrainInstar: Perform one training iteration.
iteration() - Method in class org.encog.neural.networks.training.cpn.TrainOutstar: Perform one training iteration.
iteration() - Method in class org.encog.neural.networks.training.cross.CrossValidationKFold: Perform one iteration.
iteration() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm: Perform one training iteration.
iteration() - Method in class org.encog.neural.networks.training.hebbian.HebbianTraining: Perform a single training iteration.
iteration() - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining: Perform one iteration.
iteration() - Method in class org.encog.neural.networks.training.neat.NEATTraining: Perform one training iteration.
iteration(int) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Perform the specified number of training iterations.
iteration() - Method in class org.encog.neural.networks.training.propagation.Propagation: Perform one training iteration.
iteration(int) - Method in class org.encog.neural.networks.training.propagation.Propagation: Perform the specified number of training iterations.
iteration() - Method in class org.encog.neural.networks.training.simple.TrainAdaline: Perform a training iteration.
iteration() - Method in class org.encog.neural.networks.training.svd.SVDTraining: Perform one iteration.
iteration() - Method in class org.encog.neural.networks.training.svm.SVMTrain: Perform one training iteration.
iteration() - Method in interface org.encog.neural.networks.training.Train: Perform one iteration of training.
iteration(int) - Method in interface org.encog.neural.networks.training.Train: Perform a number of training iterations.
iteration() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Called to perform one cycle of the annealing process.
iteration() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Modify the weight matrix and bias values based on the last call to calcError.
iterator() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Create an iterator for this collection.
iterator() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
iterator() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet: Get an iterator to use with the CSV data.
iterator() - Method in class org.encog.neural.data.folded.FoldedDataSet
iterator() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Get an iterator for this collection.
iterator() - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Obtain an iterator to access the collection of data.
iterator() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet

J

JacobianChainRule - Class in org.encog.neural.networks.training.lma: Calculate the Jacobian using the chain rule.
JacobianChainRule(BasicNetwork, Indexable) - Constructor for class org.encog.neural.networks.training.lma.JacobianChainRule: Construct the chain rule calculation.
jobDone(long, ConcurrentTrainingPerformerCPU) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
JobUnitContext - Class in org.encog.engine.concurrency.job: The job unit context contains context information to be passed to a job unit.
JobUnitContext() - Constructor for class org.encog.engine.concurrency.job.JobUnitContext
JobUnitWorker - Class in org.encog.engine.concurrency.job: An individual worker, that will be submitted to the thread pool.
JobUnitWorker(JobUnitContext) - Constructor for class org.encog.engine.concurrency.job.JobUnitWorker: Construct a job unit.
join() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Wait for all tasks to finish.
JordanPattern - Class in org.encog.neural.pattern: This class is used to generate an Jordan style recurrent neural network.
JordanPattern() - Constructor for class org.encog.neural.pattern.JordanPattern: Construct an object to create a Jordan type neural network.

K

kernel_type - Variable in class org.encog.mathutil.libsvm.svm_parameter
kernel_type_table - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: Constants for the kernel types.
KernelNetworkCalc - Class in org.encog.engine.opencl.kernels: An OpenCL kernel that is designed to calculate the output of a neural network.
KernelNetworkCalc(EncogCLDevice) - Constructor for class org.encog.engine.opencl.kernels.KernelNetworkCalc: Construct a kernel to train the network.
KernelNetworkTrain - Class in org.encog.engine.opencl.kernels: An OpenCL kernel that is designed to calculate gradients and help train a neural network.
KernelNetworkTrain(EncogCLDevice, FlatNetwork, EngineIndexableSet, int) - Constructor for class org.encog.engine.opencl.kernels.KernelNetworkTrain: Construct a kernel to train the network.
KernelType - Enum in org.encog.neural.networks.svm: The type of SVM kernel in use.
KernelVectorAdd - Class in org.encog.engine.opencl.kernels: A very simple kernel, used to add a vector.
KernelVectorAdd(EncogCLDevice, int) - Constructor for class org.encog.engine.opencl.kernels.KernelVectorAdd: Construct a simple kernel to add two vectors.

L

l - Variable in class org.encog.mathutil.libsvm.svm_model
l - Variable in class org.encog.mathutil.libsvm.svm_problem
label - Variable in class org.encog.mathutil.libsvm.svm_model
LAMBDA_MAX - Static variable in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining: The max amount for the LAMBDA.
LAST_DELTA - Static variable in class org.encog.neural.networks.training.propagation.back.Backpropagation: The resume key for backpropagation.
LAST_GRADIENTS - Static variable in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Continuation tag for the last gradients.
Layer - Interface in org.encog.neural.networks.layers: This interface defines all necessary methods for a neural network layer.
LayerComparator - Class in org.encog.neural.networks.structure: Used to compare layers and ensure a consistent sort order.
LayerComparator(NeuralStructure) - Constructor for class org.encog.neural.networks.structure.LayerComparator: Construct a level comparator for the specified structure.
learn() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Apply and learn.
LEARN_BPROP - Static variable in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Learn backpropagation.
LEARN_MANHATTAN - Static variable in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Learn Manhattan update rule.
LEARN_RPROP - Static variable in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Learn RPROP.
learnBPROP(double, double) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Learn using backpropagation.
LEARNING_DECAY - Static variable in class org.encog.neural.networks.training.strategy.SmartLearningRate: Learning decay rate.
LearningRate - Interface in org.encog.neural.networks.training: Specifies that a training algorithm has the concept of a learning rate.
learnLimited() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Apply and learn.
learnManhattan(double) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Learn using the Manhattan update rule.
learnRPROP() - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Learn using RPROP.
learnRPROP(double, double) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Learn using RPROP with a custom initial update and max step.
length() - Method in interface org.encog.normalize.input.HasFixedLength
length() - Method in class org.encog.normalize.input.InputFieldArray1D
length() - Method in class org.encog.normalize.input.InputFieldArray2D
LevenbergMarquardtTraining - Class in org.encog.neural.networks.training.lma: Trains a neural network using a Levenberg Marquardt algorithm (LMA).
LevenbergMarquardtTraining(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining: Construct the LMA object.
LIBSVM_VERSION - Static variable in class org.encog.mathutil.libsvm.svm
LINEAR - Static variable in class org.encog.mathutil.libsvm.svm_parameter
LinearCongruentialGenerator - Class in org.encog.mathutil: A predictable random number generator.
LinearCongruentialGenerator(long) - Constructor for class org.encog.mathutil.LinearCongruentialGenerator: Construct the default LCG.
LinearCongruentialGenerator(long, long, long, long) - Constructor for class org.encog.mathutil.LinearCongruentialGenerator: Create a LCG with the specified modulus, multiplier and increment.
Link - Class in org.encog.bot.browse.range: A document range that represents a hyperlink, and any embedded tags and text.
Link(WebPage) - Constructor for class org.encog.bot.browse.range.Link: Construct a link from the specified web page.
listToDouble(Collection<?>) - Static method in class org.encog.engine.util.EngineArray: Convert the collection to an array list of doubles.
load(InputStream) - Method in class org.encog.bot.browse.LoadWebPage: Load a web page from the specified stream.
load(String) - Method in class org.encog.bot.browse.LoadWebPage: Load the web page from a string that contains HTML.
load(URL) - Method in class org.encog.bot.rss.RSS: Load all RSS data from the specified URL.
load(Node) - Method in class org.encog.bot.rss.RSSItem: Load an item from the specified node.
load(NeuralDataSet) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Load the specified training set.
load(TickerSymbol, Set<MarketDataType>, Date, Date) - Method in interface org.encog.neural.data.market.loader.MarketLoader: Load the specified ticker symbol for the specified date.
load(TickerSymbol, Set<MarketDataType>, Date, Date) - Method in class org.encog.neural.data.market.loader.YahooFinanceLoader: Load the specified financial data.
load(Date, Date) - Method in class org.encog.neural.data.market.MarketNeuralDataSet: Load data from the loader.
load(PersistenceLocation) - Method in class org.encog.persist.EncogMemoryCollection: Load the contents of a location.
load(ReadXML) - Method in interface org.encog.persist.Persistor: Load from the specified node.
load(ReadXML) - Method in class org.encog.persist.persistors.BasicLayerPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.BasicNetworkPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.BasicNeuralDataSetPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.BufferedNeuralDataSetPersistor: Load the binary file.
load(ReadXML) - Method in class org.encog.persist.persistors.ContextLayerPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.DirectSynapsePersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.EncogScriptPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.generic.GenericPersistor: Load from the specified node.
load(ReadXML, EncogPersistedObject) - Method in class org.encog.persist.persistors.generic.XML2Object: Load an object from XML.
load(ReadXML) - Method in class org.encog.persist.persistors.OneToOneSynapsePersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.PropertyDataPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: Load a RBF layer.
load(ReadXML) - Method in class org.encog.persist.persistors.SVMNetworkPersistor: Load the SVM network.
load(ReadXML) - Method in class org.encog.persist.persistors.TextDataPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.TrainingContinuationPersistor: Load the object.
load(ReadXML) - Method in class org.encog.persist.persistors.WeightedSynapsePersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.WeightlessSynapsePersistor: Load the specified Encog object from an XML reader.
load(String) - Static method in class org.encog.util.obj.SerializeObject: Load an object.
loadActivation(String, ReadXML) - Static method in class org.encog.persist.persistors.BasicLayerPersistor
loadClassmap() - Static method in class org.encog.util.obj.ReflectionUtil: Load the classmap file.
loadContents() - Method in class org.encog.bot.browse.LoadWebPage: Using the data units, which should have already been loaded by this time, load the contents of the web page.
loadCookies(URLConnection) - Method in class org.encog.util.http.CookieUtility: Load any cookies from the specified URLConnection object.
loadCSVTOMemory(CSVFormat, String, boolean, int, int) - Static method in class org.encog.util.simple.TrainingSetUtil: Load a CSV file into a memory dataset.
loadDataUnits(InputStream) - Method in class org.encog.bot.browse.LoadWebPage: Load the data units.
LoadedMarketData - Class in org.encog.neural.data.market.loader: This class contains market data that was loaded for a specific ticker symbol and a specific date.
LoadedMarketData(Date, TickerSymbol) - Constructor for class org.encog.neural.data.market.loader.LoadedMarketData: Construct one sample of market data.
LoaderError - Exception in org.encog.neural.data.market.loader: An error that occurs when financial data is being loaded.
LoaderError(String) - Constructor for exception org.encog.neural.data.market.loader.LoaderError: Construct a message exception.
LoaderError(Throwable) - Constructor for exception org.encog.neural.data.market.loader.LoaderError: Construct an exception that holds another exception.
loadForm(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage: Called by loadContents to load a form on the page.
loadInput(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage: Called by loadContents to load an input tag on the form.
loadLink(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage: Called by loadContents to load a link on the page.
loadMatrix(ReadXML) - Static method in class org.encog.persist.persistors.PersistorUtil: Load a matrix from the reader.
loadPage(InputStream) - Static method in class org.encog.bot.BotUtil: Load load from the specified input stream.
loadPage(URL) - Static method in class org.encog.bot.BotUtil: Load the specified web page into a string.
loadString(String) - Static method in class org.encog.engine.util.ResourceLoader: Load the resource as a string.
loadString() - Method in class org.encog.persist.location.ResourcePersistence: Load the resource as a string.
loadTitle(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage: Called by loadContents to load the title of the page.
loadToMemory() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Load the binary dataset to memory.
LoadWebPage - Class in org.encog.bot.browse: Called to actually load a web page.
LoadWebPage(URL) - Constructor for class org.encog.bot.browse.LoadWebPage: Construct a web page loader with the specified base URL.
loadWorkload() - Method in class org.encog.engine.concurrency.job.ConcurrentJob: Load the subtasks.
loadWorkload() - Method in class org.encog.neural.prune.PruneIncremental: Get the next workload.
log(double) - Static method in class org.encog.engine.util.BoundMath: Calculate the log.
Logging - Class in org.encog.util.logging: Provides simple logging access to the JDK logging system.
logout() - Method in class org.encog.cloud.EncogCloud: Logout of the specified session.
LUDecomposition - Class in org.encog.mathutil.matrices.decomposition: LU Decomposition.
LUDecomposition(Matrix) - Constructor for class org.encog.mathutil.matrices.decomposition.LUDecomposition: LU Decomposition Structure to access L, U and piv.

M

magnitude(BiPolarNeuralData) - Method in class org.encog.neural.networks.logic.ART1Logic: Get the magnitude of the specified input.
main(String[]) - Static method in class org.encog.util.obj.GenerateClasslist: Run the utility.
makeSparse(NeuralData) - Method in class org.encog.neural.networks.svm.SVMNetwork: Convert regular Encog NeuralData into the "sparse" data needed by an SVM.
ManhattanPropagation - Class in org.encog.neural.networks.training.propagation.manhattan: One problem that the backpropagation technique has is that the magnitude of the partial derivative may be calculated too large or too small.
ManhattanPropagation(BasicNetwork, NeuralDataSet, double) - Constructor for class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation: Construct a Manhattan propagation training object.
ManhattanPropagation(BasicNetwork, NeuralDataSet, OpenCLTrainingProfile, double) - Constructor for class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation: Construct a Manhattan propagation training object.
MappedRange - Class in org.encog.normalize.output.mapped: Simple class that is used internally to hold a range mapping.
MappedRange(double, double, double) - Constructor for class org.encog.normalize.output.mapped.MappedRange: Construct the range mapping.
MarketDataDescription - Class in org.encog.neural.data.market: This class is used to describe the type of financial data that is needed.
MarketDataDescription(TickerSymbol, MarketDataType, TemporalDataDescription.Type, ActivationFunction, boolean, boolean) - Constructor for class org.encog.neural.data.market.MarketDataDescription: Construct a MarketDataDescription item.
MarketDataDescription(TickerSymbol, MarketDataType, TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.neural.data.market.MarketDataDescription: Construct a MarketDataDescription item.
MarketDataDescription(TickerSymbol, MarketDataType, boolean, boolean) - Constructor for class org.encog.neural.data.market.MarketDataDescription: Construct a MarketDataDescription item.
MarketDataType - Enum in org.encog.neural.data.market: The types of market data that can be used.
MarketError - Exception in org.encog.neural.data.market: Thrown when an error occurs processing market data.
MarketError(String) - Constructor for exception org.encog.neural.data.market.MarketError: Construct a message exception.
MarketError(Throwable) - Constructor for exception org.encog.neural.data.market.MarketError: Construct an exception that holds another exception.
MarketLoader - Interface in org.encog.neural.data.market.loader: This interface defines a class that can be used to load external financial data.
MarketNeuralDataSet - Class in org.encog.neural.data.market: A data set that is designed to hold market data.
MarketNeuralDataSet(MarketLoader, int, int) - Constructor for class org.encog.neural.data.market.MarketNeuralDataSet: Construct a market data set object.
MarketPoint - Class in org.encog.neural.data.market: Hold one market datapoint.
MarketPoint(Date, int) - Constructor for class org.encog.neural.data.market.MarketPoint: Construct a MarketPoint with the specified date and size.
mate(Chromosome, Chromosome, Chromosome, Chromosome) - Method in interface org.encog.solve.genetic.crossover.Crossover: Mate two chromosomes.
mate(Chromosome, Chromosome, Chromosome, Chromosome) - Method in class org.encog.solve.genetic.crossover.Splice: Assuming this chromosome is the "mother" mate with the passed in "father".
mate(Chromosome, Chromosome, Chromosome, Chromosome) - Method in class org.encog.solve.genetic.crossover.SpliceNoRepeat: Assuming this chromosome is the "mother" mate with the passed in "father".
mate(Genome, Genome, Genome) - Method in class org.encog.solve.genetic.genome.BasicGenome: Mate two genomes.
mate(Genome, Genome, Genome) - Method in interface org.encog.solve.genetic.genome.Genome: Mate with another genome and produce two children.
MateWorker - Class in org.encog.solve.genetic: This class is used in conjunction with a thread pool.
MateWorker(Genome, Genome, Genome, Genome) - Constructor for class org.encog.solve.genetic.MateWorker
MathConst - Class in org.encog.mathutil: Math constants needed by Encog.
Matrix - Class in org.encog.mathutil.matrices: This class implements a mathematical matrix.
Matrix(boolean[][]) - Constructor for class org.encog.mathutil.matrices.Matrix: Construct a bipolar matrix from an array of booleans.
Matrix(double[][]) - Constructor for class org.encog.mathutil.matrices.Matrix: Create a matrix from an array of doubles.
Matrix(int, int) - Constructor for class org.encog.mathutil.matrices.Matrix: Create a blank array with the specified number of rows and columns.
MatrixError - Exception in org.encog.mathutil.matrices: Used by the matrix classes to indicate an error.
MatrixError(String) - Constructor for exception org.encog.mathutil.matrices.MatrixError: Construct this exception with a message.
MatrixError(Throwable) - Constructor for exception org.encog.mathutil.matrices.MatrixError: Construct this exception with another exception.
MatrixMath - Class in org.encog.mathutil.matrices: This class can perform many different mathematical operations on matrixes.
MAX(double, double) - Static method in class org.encog.neural.networks.training.svd.SVD
MAX_LENGTH - Static variable in class org.encog.parse.tags.read.ReadTags: Maximum length string to read.
MAX_MOMENTUM - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum: The maximum value that momentum can go to.
MAX_PRECIS - Static variable in class org.encog.util.logging.DumpMatrix: Maximum precision.
MAX_RAND - Static variable in class org.encog.mathutil.LinearCongruentialGenerator: The maximum rand number that the standard GCC based LCG will generate.
MEMORY_GIG - Static variable in class org.encog.engine.util.Format: Bytes in a GB.
MEMORY_K - Static variable in class org.encog.engine.util.Format: Bytes in a KB.
MEMORY_MEG - Static variable in class org.encog.engine.util.Format: Bytes in a MB.
MEMORY_TERA - Static variable in class org.encog.engine.util.Format: Bytes in a TB.
mergeObjects(PersistenceLocation, String) - Method in class org.encog.persist.PersistWriter: Merge the objects from this collection into the new one.
mergeTemp() - Method in class org.encog.persist.EncogPersistedCollection: Merge the temp file with the main one, call this to make any changes permanent.
MexicanHatFunction - Class in org.encog.mathutil.rbf: Multi-dimensional Mexican Hat, or Ricker wavelet, function.
MexicanHatFunction(double, double, double) - Constructor for class org.encog.mathutil.rbf.MexicanHatFunction: Construct a single-dimension Mexican hat function with the specified peak, centers and widths.
MexicanHatFunction(double, double[], double) - Constructor for class org.encog.mathutil.rbf.MexicanHatFunction: Construct a multi-dimension Mexican hat function with the specified peak, centers and widths.
MexicanHatFunction(int) - Constructor for class org.encog.mathutil.rbf.MexicanHatFunction: Create centered at zero, width 0, and peak 0.
MILIS - Static variable in class org.encog.util.benchmark.Evaluate: Mili-seconds in a second.
MIN(int, int) - Static method in class org.encog.neural.networks.training.svd.SVD
MIN_IMPROVEMENT - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum: The minimum improvement to adjust momentum.
MIN_WORTHWHILE - Static variable in class org.encog.engine.concurrency.DetermineWorkload: What is the minimum number of workload entries for a thread to be worthwhile.
MINUTES_HOUR - Static variable in class org.encog.util.time.TimeSpan: Minutes in an hour.
MissingOpenCLAdapterError - Exception in org.encog.engine.opencl.exceptions: This error is thrown when the JOCL driver, usually a .DLL or shared library, cannot be found.
MissingOpenCLAdapterError(Throwable) - Constructor for exception org.encog.engine.opencl.exceptions.MissingOpenCLAdapterError: Construct the exception.
modifyObject(PersistenceLocation, String, String, String) - Method in class org.encog.persist.PersistWriter: Modify the specified object, such as changing its name or description.
Momentum - Interface in org.encog.neural.networks.training: Specifies that a training algorithm has the concept of a momentum.
MOMENTUM_CYCLES - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum: How many cycles to accept before adjusting momentum.
MOMENTUM_INCREASE - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum: How much to increase momentum by.
MONTHS_YEAR - Static variable in class org.encog.util.time.TimeSpan: Months in a year.
MultiplicativeGroup - Class in org.encog.normalize.output.multiplicative: Used to group multiplicative fields together.
MultiplicativeGroup() - Constructor for class org.encog.normalize.output.multiplicative.MultiplicativeGroup
multiply(double) - Method in class org.encog.mathutil.matrices.Matrix: Multiply every value in the matrix by the specified value.
multiply(double[], double[]) - Method in class org.encog.mathutil.matrices.Matrix: Multiply every row by the specified vector.
multiply(Matrix, double) - Static method in class org.encog.mathutil.matrices.MatrixMath: Return the result of multiplying every cell in the matrix by the specified value.
multiply(Matrix, Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath: Return the product of the first and second matrix.
MultiquadricFunction - Class in org.encog.mathutil.rbf: Multi-dimensional Multiquadric function.
MultiquadricFunction(double, double, double) - Constructor for class org.encog.mathutil.rbf.MultiquadricFunction: Construct a single-dimension Multiquadric function with the specified peak, centers and widths.
MultiquadricFunction(double, double[], double) - Constructor for class org.encog.mathutil.rbf.MultiquadricFunction: Construct a multi-dimension Multiquadric function with the specified peak, centers and widths.
MultiquadricFunction(int) - Constructor for class org.encog.mathutil.rbf.MultiquadricFunction: Create centered at zero, width 0, and peak 0.
MUST_USE_IMAGE - Static variable in class org.encog.neural.data.image.ImageNeuralDataSet: Error message to inform the caller that only ImageNeuralData objects can be used with this collection.
Mutate - Interface in org.encog.solve.genetic.mutate: Defines how a chromosome is mutated.
mutateActivationResponse(double, double) - Method in class org.encog.neural.networks.training.neat.NEATGenome: Mutate the activation response.
MutatePerturb - Class in org.encog.solve.genetic.mutate: A simple mutation based on random numbers.
MutatePerturb(double) - Constructor for class org.encog.solve.genetic.mutate.MutatePerturb: Construct a perturb mutation.
MutateShuffle - Class in org.encog.solve.genetic.mutate: A simple mutation where genes are shuffled.
MutateShuffle() - Constructor for class org.encog.solve.genetic.mutate.MutateShuffle
mutateWeights(double, double, double) - Method in class org.encog.neural.networks.training.neat.NEATGenome: Mutate the weights.

N

nameLayer(Layer) - Method in class org.encog.neural.networks.structure.NeuralStructure: Obtain a name for the specified layer.
navigate(Form) - Method in class org.encog.bot.browse.Browser: Navigate to the specified form by performing a submit of that form.
navigate(Form, Input) - Method in class org.encog.bot.browse.Browser: Navigate based on a form.
navigate(Link) - Method in class org.encog.bot.browse.Browser: Navigate to a new page based on a link.
navigate(String) - Method in class org.encog.bot.browse.Browser: Navigate based on a string URL.
navigate(URL) - Method in class org.encog.bot.browse.Browser: Navigate to a page based on a URL object.
navigate(URL, InputStream) - Method in class org.encog.bot.browse.Browser: Navigate to a page and post the specified data.
NEATGenome - Class in org.encog.neural.networks.training.neat: Implements a NEAT genome.
NEATGenome() - Constructor for class org.encog.neural.networks.training.neat.NEATGenome: Default constructor, used mainly for persistence.
NEATGenome(NEATGenome) - Constructor for class org.encog.neural.networks.training.neat.NEATGenome: Construct a genome by copying another.
NEATGenome(NEATTraining, long, Chromosome, Chromosome, int, int) - Constructor for class org.encog.neural.networks.training.neat.NEATGenome: Create a NEAT gnome.
NEATGenome(NEATTraining, long, int, int) - Constructor for class org.encog.neural.networks.training.neat.NEATGenome: Construct a genome, do not provide links and neurons.
NEATInnovation - Class in org.encog.neural.networks.training.neat: Implements a NEAT innovation.
NEATInnovation() - Constructor for class org.encog.neural.networks.training.neat.NEATInnovation: Default constructor, used mainly for persistence.
NEATInnovation(long, long, NEATInnovationType, long) - Constructor for class org.encog.neural.networks.training.neat.NEATInnovation: Construct an innovation.
NEATInnovation(long, long, NEATInnovationType, long, NEATNeuronType, double, double) - Constructor for class org.encog.neural.networks.training.neat.NEATInnovation: Construct an innovation.
NEATInnovation(NEATNeuronGene, long, long) - Constructor for class org.encog.neural.networks.training.neat.NEATInnovation: Construct an innovation.
NEATInnovationList - Class in org.encog.neural.networks.training.neat: Implements a NEAT innovation list.
NEATInnovationList() - Constructor for class org.encog.neural.networks.training.neat.NEATInnovationList: The default constructor, used mainly for persistance.
NEATInnovationList(Population, Chromosome, Chromosome) - Constructor for class org.encog.neural.networks.training.neat.NEATInnovationList: Construct an innovation list.
NEATInnovationType - Enum in org.encog.neural.networks.training.neat: The type of NEAT innovation.
NEATLink - Class in org.encog.neural.networks.synapse.neat: Implements a link between two NEAT neurons.
NEATLink() - Constructor for class org.encog.neural.networks.synapse.neat.NEATLink: Default constructor, used mainly for persistance.
NEATLink(double, NEATNeuron, NEATNeuron, boolean) - Constructor for class org.encog.neural.networks.synapse.neat.NEATLink: Construct a NEAT link.
NEATLinkGene - Class in org.encog.neural.networks.training.neat: Implements a NEAT link gene.
NEATLinkGene() - Constructor for class org.encog.neural.networks.training.neat.NEATLinkGene: Default constructor, used mainly for persistence.
NEATLinkGene(long, long, boolean, long, double, boolean) - Constructor for class org.encog.neural.networks.training.neat.NEATLinkGene: Construct a NEAT link gene.
NEATNeuron - Class in org.encog.neural.networks.synapse.neat: Implements a NEAT neuron.
NEATNeuron() - Constructor for class org.encog.neural.networks.synapse.neat.NEATNeuron: Default constructor, used for persistance.
NEATNeuron(NEATNeuronType, long, double, double, double) - Constructor for class org.encog.neural.networks.synapse.neat.NEATNeuron: Construct a NEAT neuron.
NEATNeuronGene - Class in org.encog.neural.networks.training.neat: Implements a NEAT neuron gene.
NEATNeuronGene() - Constructor for class org.encog.neural.networks.training.neat.NEATNeuronGene: The default constructor.
NEATNeuronGene(NEATNeuronType, long, double, double) - Constructor for class org.encog.neural.networks.training.neat.NEATNeuronGene: Construct a gene.
NEATNeuronGene(NEATNeuronType, long, double, double, boolean, double) - Constructor for class org.encog.neural.networks.training.neat.NEATNeuronGene: Construct a neuron gene.
NEATNeuronType - Enum in org.encog.neural.networks.synapse.neat: The types of neurons supported by NEAT.
NEATPattern - Class in org.encog.neural.pattern
NEATPattern() - Constructor for class org.encog.neural.pattern.NEATPattern
NEATSynapse - Class in org.encog.neural.networks.synapse.neat: Implements a NEAT network as a synapse between two layers.
NEATSynapse() - Constructor for class org.encog.neural.networks.synapse.neat.NEATSynapse: Default constructor.
NEATSynapse(BasicLayer, BasicLayer, List<NEATNeuron>, ActivationFunction, int) - Constructor for class org.encog.neural.networks.synapse.neat.NEATSynapse: Construct a NEAT synapse.
NEATSynapse(Layer, Layer) - Constructor for class org.encog.neural.networks.synapse.neat.NEATSynapse: Construct a NEAT synapse.
NEATTraining - Class in org.encog.neural.networks.training.neat: Implements NEAT genetic training.
NEATTraining(CalculateScore, BasicNetwork, Population) - Constructor for class org.encog.neural.networks.training.neat.NEATTraining: Construct a NEAT training object.
NEATTraining(CalculateScore, int, int, int) - Constructor for class org.encog.neural.networks.training.neat.NEATTraining: Construct a neat trainer with a new population.
NEATTraining(CalculateScore, Population) - Constructor for class org.encog.neural.networks.training.neat.NEATTraining: Construct neat training with a predefined population.
NEGATIVE_ETA - Static variable in class org.encog.engine.network.train.prop.RPROPConst: The NEGATIVE ETA value.
NeighborhoodBubble - Class in org.encog.neural.networks.training.competitive.neighborhood: A neighborhood function that uses a simple bubble.
NeighborhoodBubble(int) - Constructor for class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodBubble: Create a bubble neighborhood function that will return 1.0 (full update) for any neuron that is plus or minus the width distance from the winning neuron.
NeighborhoodFunction - Interface in org.encog.neural.networks.training.competitive.neighborhood: Defines how a neighborhood function should work in competitive training.
NeighborhoodRBF - Class in org.encog.neural.networks.training.competitive.neighborhood: Implements a multi-dimensional RBF neighborhood function.
NeighborhoodRBF(RBFEnum, int, int) - Constructor for class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodRBF: Construct a 2d neighborhood function based on the sizes for the x and y dimensions.
NeighborhoodRBF(int[], RadialBasisFunction) - Constructor for class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodRBF: Construct a multi-dimensional neighborhood function.
NeighborhoodSingle - Class in org.encog.neural.networks.training.competitive.neighborhood: A very simple neighborhood function that will return 1.0 (full effect) for the winning neuron, and 0.0 (no change) for everything else.
NeighborhoodSingle() - Constructor for class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingle
NeighborhoodSingleRBF - Class in org.encog.neural.networks.training.competitive.neighborhood: A neighborhood function based on an RBF function.
NeighborhoodSingleRBF(RadialBasisFunction) - Constructor for class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingleRBF: Construct the neighborhood function with the specified radial function.
network - Variable in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: The network to train.
Network - Interface in org.encog.neural.networks: Interface that defines a neural network.
NetworkCODEC - Class in org.encog.neural.networks.structure: This class will extract the "long term memory" of a neural network, that is the weights and bias values into an array.
NetworkFold - Class in org.encog.neural.networks.training.cross: The network for one fold of a cross validation.
NetworkFold(FlatNetwork) - Constructor for class org.encog.neural.networks.training.cross.NetworkFold: Construct a fold from the specified flat network.
NetworkPattern - Enum in org.encog.neural.prune: Specify which network pattern to use.
networkSize(BasicNetwork) - Static method in class org.encog.neural.networks.structure.NetworkCODEC
networkToArray(BasicNetwork) - Static method in class org.encog.neural.networks.structure.NetworkCODEC: Convert to an array.
networkToString(BasicNetwork) - Static method in class org.encog.neural.prune.PruneIncremental: Format the network as a human readable string that lists the hidden layers.
NeuralData - Interface in org.encog.neural.data: Defines an array of data.
NeuralDataError - Exception in org.encog.neural.data: Used by the neural network classes to indicate an error.
NeuralDataError(String) - Constructor for exception org.encog.neural.data.NeuralDataError: Construct a message exception.
NeuralDataError(Throwable) - Constructor for exception org.encog.neural.data.NeuralDataError: Construct an exception that holds another exception.
NeuralDataFieldHolder - Class in org.encog.normalize.input: Simple holder class used internally for Encog.
NeuralDataFieldHolder(Iterator<NeuralDataPair>, InputFieldNeuralDataSet) - Constructor for class org.encog.normalize.input.NeuralDataFieldHolder: Construct the class.
NeuralDataMapping - Class in org.encog.neural.networks: Used to map one neural data object to another.
NeuralDataMapping() - Constructor for class org.encog.neural.networks.NeuralDataMapping: Construct the neural data mapping class, with null values.
NeuralDataMapping(NeuralData, NeuralData) - Constructor for class org.encog.neural.networks.NeuralDataMapping: Construct the neural data mapping class with the specified values.
NeuralDataPair - Interface in org.encog.neural.data: Training data is stored in two ways, depending on if the data is for supervised, or unsupervised training.
NeuralDataSet - Interface in org.encog.neural.data: An interface designed to abstract classes that store neural data.
NeuralDataSetCODEC - Class in org.encog.neural.data.buffer.codec: A CODEC that works with the NeuralDataSet class.
NeuralDataSetCODEC(NeuralDataSet) - Constructor for class org.encog.neural.data.buffer.codec.NeuralDataSetCODEC: Construct a CODEC.
NeuralGeneticAlgorithm - Class in org.encog.neural.networks.training.genetic: Implements a genetic algorithm that allows a feedforward or simple recurrent neural network to be trained using a genetic algorithm.
NeuralGeneticAlgorithm(BasicNetwork, Randomizer, CalculateScore, int, double, double) - Constructor for class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm: Construct a neural genetic algorithm.
NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper - Class in org.encog.neural.networks.training.genetic: Very simple class that implements a genetic algorithm.
NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper() - Constructor for class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper
NeuralGenome - Class in org.encog.neural.networks.training.genetic: Implements a genome that allows a feedforward neural network to be trained using a genetic algorithm.
NeuralGenome(NeuralGeneticAlgorithm, BasicNetwork) - Constructor for class org.encog.neural.networks.training.genetic.NeuralGenome: Construct a neural genome.
NeuralLogic - Interface in org.encog.neural.networks.logic: Neural logic classes implement neural network logic for a variety of neural network setups.
NeuralNetworkError - Exception in org.encog.neural: Used by the neural network classes to indicate an error.
NeuralNetworkError(String) - Constructor for exception org.encog.neural.NeuralNetworkError: Construct a message exception.
NeuralNetworkError(Throwable) - Constructor for exception org.encog.neural.NeuralNetworkError: Construct an exception that holds another exception.
NeuralNetworkError(String, Throwable) - Constructor for exception org.encog.neural.NeuralNetworkError: Construct an exception that holds another exception.
NeuralNetworkPattern - Interface in org.encog.neural.pattern: Patterns are used to create common sorts of neural networks.
NeuralOutputHolder - Class in org.encog.neural.networks: Holds the output from each layer of the neural network.
NeuralOutputHolder() - Constructor for class org.encog.neural.networks.NeuralOutputHolder: Construct an empty holder.
NeuralSimulatedAnnealing - Class in org.encog.neural.networks.training.anneal: This class implements a simulated annealing training algorithm for neural networks.
NeuralSimulatedAnnealing(BasicNetwork, CalculateScore, double, double, int) - Constructor for class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Construct a simulated annleaing trainer for a feedforward neural network.
NeuralSimulatedAnnealingHelper - Class in org.encog.neural.networks.training.anneal: Simple class used by the neural simulated annealing.
NeuralSimulatedAnnealingHelper(NeuralSimulatedAnnealing) - Constructor for class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Constructs this object.
NeuralStructure - Class in org.encog.neural.networks.structure: Holds "cached" information about the structure of the neural network.
NeuralStructure(BasicNetwork) - Constructor for class org.encog.neural.networks.structure.NeuralStructure: Construct a structure object for the specified network.
next() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet.BasicNeuralIterator: Read the next item.
next() - Method in class org.encog.neural.data.buffer.BufferedDataSetIterator
next() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet.CSVNeuralIterator: Read the next record from the CSV file.
next() - Method in class org.encog.neural.data.folded.FoldedIterator
next() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet.SQLNeuralIterator: Read the next row from the database.
next() - Method in class org.encog.neural.data.union.UnionNeuralDataSet.UnionIterator: Obtain the next piece of data.
next() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet.XMLNeuralIterator: Read the next training set item.
next() - Method in class org.encog.util.csv.ReadCSV: Read the next line.
nextDouble() - Method in class org.encog.mathutil.LinearCongruentialGenerator
nextDouble() - Method in class org.encog.mathutil.randomize.BasicRandomizer
nextDouble(double, double) - Method in class org.encog.mathutil.randomize.BasicRandomizer: Generate a random number in the specified range.
nextLong() - Method in class org.encog.mathutil.LinearCongruentialGenerator
NguyenWidrowRandomizer - Class in org.encog.mathutil.randomize: Implementation of Nguyen-Widrow weight initialization.
NguyenWidrowRandomizer(double, double) - Constructor for class org.encog.mathutil.randomize.NguyenWidrowRandomizer: Construct a Nguyen-Widrow randomizer.
NO_BIAS_ACTIVATION - Static variable in class org.encog.engine.network.flat.FlatNetwork: The value that indicates that there is no bias activation.
NominalItem - Class in org.encog.normalize.output.nominal: A nominal item.
NominalItem() - Constructor for class org.encog.normalize.output.nominal.NominalItem: Construct a empty range item.
NominalItem(InputField, double, double) - Constructor for class org.encog.normalize.output.nominal.NominalItem: Create a nominal item.
norm2() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition: Two norm
NormalizationError - Exception in org.encog.normalize: Used for normalization errors.
NormalizationError(String) - Constructor for exception org.encog.normalize.NormalizationError: Construct a message exception.
NormalizationError(Throwable) - Constructor for exception org.encog.normalize.NormalizationError: Construct an exception that holds another exception.
NormalizationStorage - Interface in org.encog.normalize.target: Defines a means by which normalized data can be stored.
NormalizationStorageArray1D - Class in org.encog.normalize.target: Output the normalized data to a 1D array.
NormalizationStorageArray1D() - Constructor for class org.encog.normalize.target.NormalizationStorageArray1D
NormalizationStorageArray1D(double[]) - Constructor for class org.encog.normalize.target.NormalizationStorageArray1D: Construct an object to store to a 2D array.
NormalizationStorageArray2D - Class in org.encog.normalize.target: Output the normalized data to a 2D array.
NormalizationStorageArray2D(double[][]) - Constructor for class org.encog.normalize.target.NormalizationStorageArray2D: Construct an object to store to a 2D array.
NormalizationStorageArray2D() - Constructor for class org.encog.normalize.target.NormalizationStorageArray2D
NormalizationStorageCSV - Class in org.encog.normalize.target: Store normalized data to a CSV file.
NormalizationStorageCSV(CSVFormat, File) - Constructor for class org.encog.normalize.target.NormalizationStorageCSV: Construct a CSV storage object from the specified file.
NormalizationStorageCSV() - Constructor for class org.encog.normalize.target.NormalizationStorageCSV
NormalizationStorageCSV(File) - Constructor for class org.encog.normalize.target.NormalizationStorageCSV: Construct a CSV storage object from the specified file.
NormalizationStorageEncogCollection - Class in org.encog.normalize.target
NormalizationStorageEncogCollection() - Constructor for class org.encog.normalize.target.NormalizationStorageEncogCollection
NormalizationStorageNeuralDataSet - Class in org.encog.normalize.target: Store the normalized data to a neural data set.
NormalizationStorageNeuralDataSet() - Constructor for class org.encog.normalize.target.NormalizationStorageNeuralDataSet
NormalizationStorageNeuralDataSet(int, int) - Constructor for class org.encog.normalize.target.NormalizationStorageNeuralDataSet: Construct a new NeuralDataSet based on the parameters specified.
NormalizationStorageNeuralDataSet(NeuralDataSet) - Constructor for class org.encog.normalize.target.NormalizationStorageNeuralDataSet: Construct a normalized neural storage class to hold data.
normalizeBinary(double) - Static method in class org.encog.mathutil.matrices.BiPolarUtil: Normalize a binary number.
nr_class - Variable in class org.encog.mathutil.libsvm.svm_model
nr_weight - Variable in class org.encog.mathutil.libsvm.svm_parameter
nSV - Variable in class org.encog.mathutil.libsvm.svm_model
nu - Variable in class org.encog.mathutil.libsvm.svm_parameter
NU_SVC - Static variable in class org.encog.mathutil.libsvm.svm_parameter
NU_SVR - Static variable in class org.encog.mathutil.libsvm.svm_parameter
NullStatusReportable - Class in org.encog: A report object that does nothing.
NullStatusReportable() - Constructor for class org.encog.NullStatusReportable
NumberList - Class in org.encog.util.csv: Class used to handle lists of numbers.
NumericRange - Class in org.encog.mathutil: A numeric range has a high, low, mean, root-mean-square, standard deviation, and the count of how many samples it contains.
NumericRange(List<Double>) - Constructor for class org.encog.mathutil.NumericRange: Create a numeric range from a list of values.

O

Object2XML - Class in org.encog.persist.persistors.generic: A generic class used to take an object and produce XML for it.
Object2XML() - Constructor for class org.encog.persist.persistors.generic.Object2XML
ObjectCloner - Class in org.encog.util.obj: A simple Object cloner that uses serialization.
ObjectMapper - Class in org.encog.persist.persistors.generic: Used to map objects to reference numbers.
ObjectMapper() - Constructor for class org.encog.persist.persistors.generic.ObjectMapper
ObjectPair<A,B> - Class in org.encog.engine.util: A pair of objects.
ObjectPair(A, B) - Constructor for class org.encog.engine.util.ObjectPair: Construct an object pair.
ObjectTagger - Class in org.encog.persist.persistors.generic: The object tagger is used in generic persistence to tag objects with a reference number.
ObjectTagger() - Constructor for class org.encog.persist.persistors.generic.ObjectTagger
objectToDouble(Double[]) - Static method in class org.encog.engine.util.EngineArray: Convert an array of Double objects to double primitives.
obtainPair() - Method in class org.encog.normalize.input.NeuralDataFieldHolder: Obtain the next pair.
ONE_CLASS - Static variable in class org.encog.mathutil.libsvm.svm_parameter
OneToOneSynapse - Class in org.encog.neural.networks.synapse: A one-to-one synapse requires that the from and to layers have exactly the same number of neurons.
OneToOneSynapse() - Constructor for class org.encog.neural.networks.synapse.OneToOneSynapse: Simple default constructor.
OneToOneSynapse(Layer, Layer) - Constructor for class org.encog.neural.networks.synapse.OneToOneSynapse: Construct a one-to-one synapse between the two layers.
OneToOneSynapsePersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the OneToOneSynapse class.
OneToOneSynapsePersistor() - Constructor for class org.encog.persist.persistors.OneToOneSynapsePersistor
open() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Open the binary file for reading.
open() - Method in class org.encog.neural.data.buffer.EncogEGBFile: OPen an existing EGB file.
open(DataNormalization) - Method in interface org.encog.normalize.target.NormalizationStorage: Close the storage.
open(DataNormalization) - Method in class org.encog.normalize.target.NormalizationStorageArray1D: Not needed for this storage type.
open(DataNormalization) - Method in class org.encog.normalize.target.NormalizationStorageArray2D: Not needed for this storage type.
open(DataNormalization) - Method in class org.encog.normalize.target.NormalizationStorageCSV: Open the CSV file.
open(DataNormalization) - Method in class org.encog.normalize.target.NormalizationStorageEncogCollection
open(DataNormalization) - Method in class org.encog.normalize.target.NormalizationStorageNeuralDataSet: Not needed for this storage type.
openAdditional() - Method in class org.encog.engine.data.BasicEngineDataSet: Create an additional data set.
openAdditional() - Method in interface org.encog.engine.data.EngineIndexableSet: Opens an additional instance of this dataset.
openAdditional() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Create an additional data set.
openAdditional() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
openAdditional() - Method in class org.encog.neural.data.folded.FoldedDataSet: Opens an additional instance of this dataset.
OpenCLError - Exception in org.encog.engine.opencl.exceptions: Thrown when an OpenCL error occurs.
OpenCLError(String) - Constructor for exception org.encog.engine.opencl.exceptions.OpenCLError: Construct a message exception.
OpenCLError(String, Throwable) - Constructor for exception org.encog.engine.opencl.exceptions.OpenCLError: Construct an exception that holds another exception.
OpenCLError(Throwable) - Constructor for exception org.encog.engine.opencl.exceptions.OpenCLError: Construct an exception that holds another exception.
OpenCLTrainingProfile - Class in org.encog.engine.network.train.prop: Specifies a training profile for an OpenCL training session.
OpenCLTrainingProfile(EncogCLDevice) - Constructor for class org.encog.engine.network.train.prop.OpenCLTrainingProfile: Construct a training profile with the specified device and the value of one for all ratios.
OpenCLTrainingProfile(EncogCLDevice, double, int, double) - Constructor for class org.encog.engine.network.train.prop.OpenCLTrainingProfile: Construct a training profile.
org.encog - package org.encog
org.encog.bot - package org.encog.bot
org.encog.bot.browse - package org.encog.bot.browse
org.encog.bot.browse.range - package org.encog.bot.browse.range
org.encog.bot.dataunit - package org.encog.bot.dataunit
org.encog.bot.rss - package org.encog.bot.rss
org.encog.cloud - package org.encog.cloud
org.encog.engine - package org.encog.engine
org.encog.engine.concurrency - package org.encog.engine.concurrency
org.encog.engine.concurrency.calc - package org.encog.engine.concurrency.calc
org.encog.engine.concurrency.job - package org.encog.engine.concurrency.job
org.encog.engine.data - package org.encog.engine.data
org.encog.engine.network.activation - package org.encog.engine.network.activation
org.encog.engine.network.flat - package org.encog.engine.network.flat
org.encog.engine.network.rbf - package org.encog.engine.network.rbf
org.encog.engine.network.train - package org.encog.engine.network.train
org.encog.engine.network.train.gradient - package org.encog.engine.network.train.gradient
org.encog.engine.network.train.prop - package org.encog.engine.network.train.prop
org.encog.engine.opencl - package org.encog.engine.opencl
org.encog.engine.opencl.exceptions - package org.encog.engine.opencl.exceptions
org.encog.engine.opencl.kernels - package org.encog.engine.opencl.kernels
org.encog.engine.util - package org.encog.engine.util
org.encog.engine.validate - package org.encog.engine.validate
org.encog.mathutil - package org.encog.mathutil
org.encog.mathutil.libsvm - package org.encog.mathutil.libsvm
org.encog.mathutil.matrices - package org.encog.mathutil.matrices
org.encog.mathutil.matrices.decomposition - package org.encog.mathutil.matrices.decomposition
org.encog.mathutil.randomize - package org.encog.mathutil.randomize
org.encog.mathutil.rbf - package org.encog.mathutil.rbf
org.encog.neural - package org.encog.neural
org.encog.neural.data - package org.encog.neural.data
org.encog.neural.data.basic - package org.encog.neural.data.basic
org.encog.neural.data.bipolar - package org.encog.neural.data.bipolar
org.encog.neural.data.buffer - package org.encog.neural.data.buffer
org.encog.neural.data.buffer.codec - package org.encog.neural.data.buffer.codec
org.encog.neural.data.csv - package org.encog.neural.data.csv
org.encog.neural.data.folded - package org.encog.neural.data.folded
org.encog.neural.data.image - package org.encog.neural.data.image
org.encog.neural.data.market - package org.encog.neural.data.market
org.encog.neural.data.market.loader - package org.encog.neural.data.market.loader
org.encog.neural.data.sql - package org.encog.neural.data.sql
org.encog.neural.data.temporal - package org.encog.neural.data.temporal
org.encog.neural.data.union - package org.encog.neural.data.union
org.encog.neural.data.xml - package org.encog.neural.data.xml
org.encog.neural.networks - package org.encog.neural.networks
org.encog.neural.networks.layers - package org.encog.neural.networks.layers
org.encog.neural.networks.logic - package org.encog.neural.networks.logic
org.encog.neural.networks.structure - package org.encog.neural.networks.structure
org.encog.neural.networks.svm - package org.encog.neural.networks.svm
org.encog.neural.networks.synapse - package org.encog.neural.networks.synapse
org.encog.neural.networks.synapse.neat - package org.encog.neural.networks.synapse.neat
org.encog.neural.networks.training - package org.encog.neural.networks.training
org.encog.neural.networks.training.anneal - package org.encog.neural.networks.training.anneal
org.encog.neural.networks.training.competitive - package org.encog.neural.networks.training.competitive
org.encog.neural.networks.training.competitive.neighborhood - package org.encog.neural.networks.training.competitive.neighborhood
org.encog.neural.networks.training.concurrent - package org.encog.neural.networks.training.concurrent
org.encog.neural.networks.training.concurrent.jobs - package org.encog.neural.networks.training.concurrent.jobs
org.encog.neural.networks.training.concurrent.performers - package org.encog.neural.networks.training.concurrent.performers
org.encog.neural.networks.training.cpn - package org.encog.neural.networks.training.cpn
org.encog.neural.networks.training.cross - package org.encog.neural.networks.training.cross
org.encog.neural.networks.training.genetic - package org.encog.neural.networks.training.genetic
org.encog.neural.networks.training.hebbian - package org.encog.neural.networks.training.hebbian
org.encog.neural.networks.training.lma - package org.encog.neural.networks.training.lma
org.encog.neural.networks.training.neat - package org.encog.neural.networks.training.neat
org.encog.neural.networks.training.propagation - package org.encog.neural.networks.training.propagation
org.encog.neural.networks.training.propagation.back - package org.encog.neural.networks.training.propagation.back
org.encog.neural.networks.training.propagation.manhattan - package org.encog.neural.networks.training.propagation.manhattan
org.encog.neural.networks.training.propagation.resilient - package org.encog.neural.networks.training.propagation.resilient
org.encog.neural.networks.training.propagation.scg - package org.encog.neural.networks.training.propagation.scg
org.encog.neural.networks.training.simple - package org.encog.neural.networks.training.simple
org.encog.neural.networks.training.strategy - package org.encog.neural.networks.training.strategy
org.encog.neural.networks.training.strategy.end - package org.encog.neural.networks.training.strategy.end
org.encog.neural.networks.training.svd - package org.encog.neural.networks.training.svd
org.encog.neural.networks.training.svm - package org.encog.neural.networks.training.svm
org.encog.neural.pattern - package org.encog.neural.pattern
org.encog.neural.prune - package org.encog.neural.prune
org.encog.normalize - package org.encog.normalize
org.encog.normalize.input - package org.encog.normalize.input
org.encog.normalize.output - package org.encog.normalize.output
org.encog.normalize.output.mapped - package org.encog.normalize.output.mapped
org.encog.normalize.output.multiplicative - package org.encog.normalize.output.multiplicative
org.encog.normalize.output.nominal - package org.encog.normalize.output.nominal
org.encog.normalize.output.zaxis - package org.encog.normalize.output.zaxis
org.encog.normalize.segregate - package org.encog.normalize.segregate
org.encog.normalize.segregate.index - package org.encog.normalize.segregate.index
org.encog.normalize.target - package org.encog.normalize.target
org.encog.parse - package org.encog.parse
org.encog.parse.tags - package org.encog.parse.tags
org.encog.parse.tags.read - package org.encog.parse.tags.read
org.encog.parse.tags.write - package org.encog.parse.tags.write
org.encog.persist - package org.encog.persist
org.encog.persist.annotations - package org.encog.persist.annotations
org.encog.persist.location - package org.encog.persist.location
org.encog.persist.persistors - package org.encog.persist.persistors
org.encog.persist.persistors.generic - package org.encog.persist.persistors.generic
org.encog.script - package org.encog.script
org.encog.solve.anneal - package org.encog.solve.anneal
org.encog.solve.genetic - package org.encog.solve.genetic
org.encog.solve.genetic.crossover - package org.encog.solve.genetic.crossover
org.encog.solve.genetic.genes - package org.encog.solve.genetic.genes
org.encog.solve.genetic.genome - package org.encog.solve.genetic.genome
org.encog.solve.genetic.innovation - package org.encog.solve.genetic.innovation
org.encog.solve.genetic.mutate - package org.encog.solve.genetic.mutate
org.encog.solve.genetic.population - package org.encog.solve.genetic.population
org.encog.solve.genetic.selection - package org.encog.solve.genetic.selection
org.encog.solve.genetic.species - package org.encog.solve.genetic.species
org.encog.util - package org.encog.util
org.encog.util.benchmark - package org.encog.util.benchmark
org.encog.util.csv - package org.encog.util.csv
org.encog.util.downsample - package org.encog.util.downsample
org.encog.util.file - package org.encog.util.file
org.encog.util.http - package org.encog.util.http
org.encog.util.identity - package org.encog.util.identity
org.encog.util.logging - package org.encog.util.logging
org.encog.util.obj - package org.encog.util.obj
org.encog.util.simple - package org.encog.util.simple
org.encog.util.time - package org.encog.util.time
OutOfOpenCLResources - Exception in org.encog.engine.opencl.exceptions: This exception is thrown when the underlying OpenCL system returns with the CL_OUT_OF_RESOURCES.
OutOfOpenCLResources(Throwable) - Constructor for exception org.encog.engine.opencl.exceptions.OutOfOpenCLResources: Construct the exception.
OutputEquilateral - Class in org.encog.normalize.output.nominal: Allows nominal items to be encoded using the equilateral method.
OutputEquilateral() - Constructor for class org.encog.normalize.output.nominal.OutputEquilateral: Prodvide a default constructor for reflection.
OutputEquilateral(double, double) - Constructor for class org.encog.normalize.output.nominal.OutputEquilateral: Create an equilateral output field with the specified high and low output values.
OutputField - Interface in org.encog.normalize.output: An output field, this represents the actual output from the normalization.
OutputFieldDirect - Class in org.encog.normalize.output: A direct output field, will simply pass the input value to the output.
OutputFieldDirect(InputField) - Constructor for class org.encog.normalize.output.OutputFieldDirect: Construct a direct output field.
OutputFieldDirect() - Constructor for class org.encog.normalize.output.OutputFieldDirect: Default constructor, used for reflection.
OutputFieldEncode - Class in org.encog.normalize.output.mapped: An encoded output field.
OutputFieldEncode(InputField) - Constructor for class org.encog.normalize.output.mapped.OutputFieldEncode: Construct an encoded field.
OutputFieldGroup - Interface in org.encog.normalize.output: Output fields can be grouped together if they are calculated together.
OutputFieldGrouped - Class in org.encog.normalize.output: Defines an output field that can be grouped.
OutputFieldGrouped() - Constructor for class org.encog.normalize.output.OutputFieldGrouped: Default constructor, used mainly for reflection.
OutputFieldGrouped(OutputFieldGroup, InputField) - Constructor for class org.encog.normalize.output.OutputFieldGrouped: Construct a grouped output field.
OutputFieldMultiplicative - Class in org.encog.normalize.output.multiplicative: Both the multiplicative and z-axis normalization types allow a group of outputs to be adjusted so that the "vector length" is 1.
OutputFieldMultiplicative() - Constructor for class org.encog.normalize.output.multiplicative.OutputFieldMultiplicative: The default constructor.
OutputFieldMultiplicative(OutputFieldGroup, InputField) - Constructor for class org.encog.normalize.output.multiplicative.OutputFieldMultiplicative: Construct a multiplicative output field.
OutputFieldRangeMapped - Class in org.encog.normalize.output: A ranged mapped output field.
OutputFieldRangeMapped() - Constructor for class org.encog.normalize.output.OutputFieldRangeMapped: Default constructor, used mainly for reflection.
OutputFieldRangeMapped(InputField, double, double) - Constructor for class org.encog.normalize.output.OutputFieldRangeMapped: Construct a range mapped output field.
OutputFieldZAxis - Class in org.encog.normalize.output.zaxis: Both the multiplicative and z-axis normalization types allow a group of outputs to be adjusted so that the "vector length" is 1.
OutputFieldZAxis(OutputFieldGroup, InputField) - Constructor for class org.encog.normalize.output.zaxis.OutputFieldZAxis: Construct a ZAxis output field.
OutputFieldZAxisSynthetic - Class in org.encog.normalize.output.zaxis: This field represents the synthetic value used in Z-Axis normalization.
OutputFieldZAxisSynthetic(OutputFieldGroup) - Constructor for class org.encog.normalize.output.zaxis.OutputFieldZAxisSynthetic: Construct a synthetic output field for Z-Axis.
OutputOneOf - Class in org.encog.normalize.output.nominal: An output field that uses the "on of" technique to represent input data.
OutputOneOf() - Constructor for class org.encog.normalize.output.nominal.OutputOneOf: Default constructor for reflection.
OutputOneOf(double, double) - Constructor for class org.encog.normalize.output.nominal.OutputOneOf: Construct a one-of field and specify the true and false value.
OutputStreamPersistence - Class in org.encog.persist.location: This class allows Encog persistence to use a location that is based on an OutputStream.
OutputStreamPersistence(OutputStream) - Constructor for class org.encog.persist.location.OutputStreamPersistence: Construct the output stream location.

P

p - Variable in class org.encog.mathutil.libsvm.svm_parameter
param - Variable in class org.encog.mathutil.libsvm.svm_model
PARAM_COMPETITIVE_MAX_WINNERS - Static variable in class org.encog.engine.network.activation.ActivationCompetitive: The offset to the parameter that holds the max winners.
PARAM_GAUSSIAN_CENTER - Static variable in class org.encog.engine.network.activation.ActivationGaussian: The offset to the parameter that holds the width.
PARAM_GAUSSIAN_PEAK - Static variable in class org.encog.engine.network.activation.ActivationGaussian: The offset to the parameter that holds the peak.
PARAM_GAUSSIAN_WIDTH - Static variable in class org.encog.engine.network.activation.ActivationGaussian: The offset to the parameter that holds the width.
PARAM_LINEAR_SLOPE - Static variable in class org.encog.engine.network.activation.ActivationLinear: The offset to the parameter that holds the linear slope.
PARAM_RAMP_HIGH - Static variable in class org.encog.engine.network.activation.ActivationRamp: The ramp high parameter.
PARAM_RAMP_HIGH_THRESHOLD - Static variable in class org.encog.engine.network.activation.ActivationRamp: The ramp high threshold parameter.
PARAM_RAMP_LOW - Static variable in class org.encog.engine.network.activation.ActivationRamp: The ramp low parameter.
PARAM_RAMP_LOW_THRESHOLD - Static variable in class org.encog.engine.network.activation.ActivationRamp: The ramp low threshold parameter.
PARAM_STEP_CENTER - Static variable in class org.encog.engine.network.activation.ActivationStep: The step center parameter.
PARAM_STEP_HIGH - Static variable in class org.encog.engine.network.activation.ActivationStep: The step high parameter.
PARAM_STEP_LOW - Static variable in class org.encog.engine.network.activation.ActivationStep: The step low parameter.
ParentSelection - Interface in org.encog.solve.genetic.selection: Will be expanded in the future.
PARRAY_INPUT_COUNT - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkCalc: The input count.
PARRAY_INPUT_COUNT - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkTrain: The input count.
PARRAY_ITEMS_PER - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkCalc: Items to train per call.
PARRAY_ITEMS_PER - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkTrain: Items to train per call.
PARRAY_ITERATIONS - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkCalc: Items to train per call.
PARRAY_ITERATIONS - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkTrain: Items to train per call.
PARRAY_LAYER_COUNT - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkCalc: The layer count.
PARRAY_LAYER_COUNT - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkTrain: The layer count.
PARRAY_LEARN - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkCalc: Are we learning? 0=no, 1 =yes.
PARRAY_LEARN - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkTrain: Are we learning? 0=no, 1 =yes.
PARRAY_OUTPUT_COUNT - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkCalc: The output count.
PARRAY_OUTPUT_COUNT - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkTrain: The output count.
PARRAY_START - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkCalc: What is the starting index to train at.
PARRAY_START - Static variable in class org.encog.engine.opencl.kernels.KernelNetworkTrain: What is the starting index to train at.
parse(String) - Method in class org.encog.util.csv.CSVFormat: Parse the specified string to a double.
parse(String) - Static method in class org.encog.util.http.FormUtility: Parse a URL query string.
parseAttributeName() - Method in class org.encog.parse.tags.read.ReadHTML: Parse the attribute name.
parseAttributeName() - Method in class org.encog.parse.tags.read.ReadTags: Parse an attribute name, if one is present.
parseDate(String) - Static method in class org.encog.bot.rss.RSS: Simple utility function that converts a RSS formatted date into a Java date.
parseDate(String) - Static method in class org.encog.util.csv.ReadCSV: Parse a date.
ParseError - Exception in org.encog.parse: Indicates an error has occured in one of the parsers.
ParseError(String) - Constructor for exception org.encog.parse.ParseError: Construct a message exception.
ParseError(Throwable) - Constructor for exception org.encog.parse.ParseError: Construct an exception that holds another exception.
parseString() - Method in class org.encog.parse.tags.read.ReadTags: Called to parse a double or single quote string.
parseTag() - Method in class org.encog.parse.tags.read.ReadTags: Called when a tag is detected.
passInit() - Method in class org.encog.normalize.segregate.index.IndexSegregator: Reset the counter to zero.
passInit() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator: Init for a new pass.
passInit() - Method in class org.encog.normalize.segregate.RangeSegregator: Nothing needs to be done to setup for a pass.
passInit() - Method in interface org.encog.normalize.segregate.Segregator: Init for a pass.
PatternConst - Class in org.encog.neural.pattern: GUI constants for creating the patterns.
PatternError - Exception in org.encog.neural.pattern: This class is thrown when an error occurs while using one of the neural network pattern classes.
PatternError(String) - Constructor for exception org.encog.neural.pattern.PatternError: Construct a message exception.
PatternError(Throwable) - Constructor for exception org.encog.neural.pattern.PatternError: Construct an exception that holds another exception.
pause() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation: Pause the training.
pause() - Method in class org.encog.neural.networks.training.propagation.Propagation: Pause the training to continue later.
pause() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Pause the training.
peek() - Method in class org.encog.parse.PeekableInputStream: Peek at the next character from the stream.
peek(int) - Method in class org.encog.parse.PeekableInputStream: Peek at a specified depth.
peek(String) - Method in class org.encog.parse.PeekableInputStream: Peek ahead and see if the specified string is present.
PeekableInputStream - Class in org.encog.parse: This is a special input stream that allows the program to peek one or more characters ahead in the file.
PeekableInputStream(InputStream) - Constructor for class org.encog.parse.PeekableInputStream: The constructor accepts an InputStream to setup the object.
perform(TrainingJob) - Method in interface org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformer: Perform the specified job.
perform(TrainingJob) - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU: Perform the specified job.
PerformerTask - Class in org.encog.neural.networks.training.concurrent.performers
PerformerTask(ConcurrentTrainingPerformer) - Constructor for class org.encog.neural.networks.training.concurrent.performers.PerformerTask
performJobUnit(JobUnitContext) - Method in class org.encog.engine.concurrency.job.ConcurrentJob: Perform one job unit.
performJobUnit(JobUnitContext) - Method in class org.encog.neural.prune.PruneIncremental: Perform an individual job unit, which is a single network to train and evaluate.
performMutation(Chromosome) - Method in interface org.encog.solve.genetic.mutate.Mutate: Perform a mutation on the specified chromosome.
performMutation(Chromosome) - Method in class org.encog.solve.genetic.mutate.MutatePerturb: Perform a perturb mutation on the specified chromosome.
performMutation(Chromosome) - Method in class org.encog.solve.genetic.mutate.MutateShuffle: Perform a shuffle mutation.
performURLGET(boolean, String) - Method in class org.encog.cloud.CloudRequest: Perform a GET request.
performURLPOST(boolean, String, Map<String, String>) - Method in class org.encog.cloud.CloudRequest: Perform a POST to the cloud.
PersistenceLocation - Interface in org.encog.persist.location: A persistence location specifies how the persistence collection is stored.
PersistError - Exception in org.encog.persist: General error class for Encog persistence.
PersistError(String) - Constructor for exception org.encog.persist.PersistError: Construct a message exception.
PersistError(String, Throwable) - Constructor for exception org.encog.persist.PersistError: Construct an exception that holds another exception.
PersistError(Throwable) - Constructor for exception org.encog.persist.PersistError: Construct an exception that holds another exception.
Persistor - Interface in org.encog.persist: This interface defines a class that can load and save an EncogPersistedObject.
PersistorUtil - Class in org.encog.persist.persistors: This class contains some utilities for persisting objects.
PersistReader - Class in org.encog.persist: Utility class for reading Encog persited object files.
PersistReader(PersistenceLocation) - Constructor for class org.encog.persist.PersistReader: Construct a persist reader.
PersistWriter - Class in org.encog.persist: Utility class for writing Encog persisted class files.
PersistWriter(PersistenceLocation) - Constructor for class org.encog.persist.PersistWriter: Create a writer for the specified location.
plural(TimeUnit) - Method in class org.encog.util.time.EnglishTimeUnitNames: Get the plural form for a TimeUnit.
plural(TimeUnit) - Method in interface org.encog.util.time.TimeUnitNames: Get the plural name for the specified time unit.
POLY - Static variable in class org.encog.mathutil.libsvm.svm_parameter
PoolItem - Class in org.encog.engine.concurrency: An Encog task being executed by the Java thread pool.
PoolItem(EngineTask, TaskGroup) - Constructor for class org.encog.engine.concurrency.PoolItem: Create a pool item.
Population - Interface in org.encog.solve.genetic.population: Defines a population of genomes.
POSITIVE_ETA - Static variable in class org.encog.engine.network.train.prop.RPROPConst: The POSITIVE ETA value.
postIteration() - Method in class org.encog.neural.networks.training.BasicTraining: Call the strategies after an iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.end.EndIterationsStrategy: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.end.EndMaxErrorStrategy: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.end.EndMinutesStrategy: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.Greedy: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.HybridStrategy: Called just after a training iteration.
postIteration() - Method in interface org.encog.neural.networks.training.Strategy: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.RequiredImprovementStrategy: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.ResetStrategy: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.SmartLearningRate: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.SmartMomentum: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.StopTrainingStrategy: Called just after a training iteration.
pow(double, double) - Static method in class org.encog.engine.util.BoundMath: Calculate the power of a number.
PRECOMPUTED - Static variable in class org.encog.mathutil.libsvm.svm_parameter
preIteration() - Method in class org.encog.neural.networks.training.BasicTraining: Call the strategies before an iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.end.EndIterationsStrategy: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.end.EndMaxErrorStrategy: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.end.EndMinutesStrategy: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.Greedy: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.HybridStrategy: Called just before a training iteration.
preIteration() - Method in interface org.encog.neural.networks.training.Strategy: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.RequiredImprovementStrategy: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.ResetStrategy: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.SmartLearningRate: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.SmartMomentum: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.StopTrainingStrategy: Called just before a training iteration.
prepareKernel() - Method in class org.encog.engine.opencl.kernels.EncogKernel: Called internally to prepare to execute a kernel.
prepareRead() - Method in class org.encog.neural.data.buffer.codec.ArrayDataCODEC: Prepare to read from an external data source.
prepareRead() - Method in class org.encog.neural.data.buffer.codec.CSVDataCODEC: Prepare to read from the CSV file.
prepareRead() - Method in interface org.encog.neural.data.buffer.codec.DataSetCODEC: Prepare to read from an external data source.
prepareRead() - Method in class org.encog.neural.data.buffer.codec.ExcelCODEC: Prepare to read from an external data source.
prepareRead() - Method in class org.encog.neural.data.buffer.codec.NeuralDataSetCODEC: Prepare to read from an external data source.
prepareWrite(int, int, int) - Method in class org.encog.neural.data.buffer.codec.ArrayDataCODEC: Prepare to write to an external data destination.
prepareWrite(int, int, int) - Method in class org.encog.neural.data.buffer.codec.CSVDataCODEC: Prepare to write to a CSV file.
prepareWrite(int, int, int) - Method in interface org.encog.neural.data.buffer.codec.DataSetCODEC: Prepare to write to an external data destination.
prepareWrite(int, int, int) - Method in class org.encog.neural.data.buffer.codec.ExcelCODEC: Prepare to write to an external data destination.
prepareWrite(int, int, int) - Method in class org.encog.neural.data.buffer.codec.NeuralDataSetCODEC: Prepare to write to an external data destination.
preprocessLayer(Layer, NeuralData, Synapse) - Method in class org.encog.neural.networks.logic.FeedforwardLogic: Can be overridden by subclasses.
preprocessLayer(Layer, NeuralData, Synapse) - Method in class org.encog.neural.networks.logic.SimpleRecurrentLogic: Handle recurrent layers.
print(String) - Method in interface org.encog.mathutil.libsvm.svm_print_interface
print(String) - Method in interface org.encog.script.ConsoleInputOutput
print(String) - Method in class org.encog.script.StandardConsole
printLine(String) - Method in interface org.encog.script.ConsoleInputOutput
printLine(String) - Method in class org.encog.script.StandardConsole
probA - Variable in class org.encog.mathutil.libsvm.svm_model
probability - Variable in class org.encog.mathutil.libsvm.svm_parameter
probB - Variable in class org.encog.mathutil.libsvm.svm_model
process() - Method in class org.encog.engine.concurrency.job.ConcurrentJob: Process the job.
process(NeuralData) - Method in class org.encog.neural.networks.layers.BasicLayer: Process the input pattern.
process(NeuralData) - Method in class org.encog.neural.networks.layers.ContextLayer: Called to process input from the previous layer.
process(NeuralData) - Method in interface org.encog.neural.networks.layers.Layer: Process the data before it is modified by this layer.
process() - Method in class org.encog.neural.prune.PruneIncremental: Begin the prune process.
process() - Method in class org.encog.normalize.DataNormalization: Call this method to begin the normalization process.
process() - Method in class org.encog.util.benchmark.EncogBenchmark: Perform the benchmark.
processImage(Image) - Method in interface org.encog.util.downsample.Downsample: Process the specified image.
processImage(Image) - Method in class org.encog.util.downsample.RGBDownsample: Process the image and prepare it to be downsampled.
processTask(EngineTask) - Method in class org.encog.engine.concurrency.EngineConcurrency: Process the specified task.
processTask(EngineTask, TaskGroup) - Method in class org.encog.engine.concurrency.EngineConcurrency: Process the specified task.
Propagation - Class in org.encog.neural.networks.training.propagation: Implements basic functionality that is needed by each of the propagation methods.
Propagation(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.propagation.Propagation: Construct a propagation object.
PROPERTY_A1 - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the A1 parameter.
PROPERTY_ANNEAL_CYCLES - Static variable in class org.encog.neural.networks.logic.BoltzmannLogic: Neural network property, the number of annealing cycles to run.
PROPERTY_B1 - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the B1 parameter.
PROPERTY_BIAS_ACTIVATION - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The bias activation.
PROPERTY_C1 - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the C1 parameter.
PROPERTY_CENTERS - Static variable in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: The centers.
PROPERTY_CONTEXT - Variable in class org.encog.persist.persistors.ContextLayerPersistor
PROPERTY_D1 - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the D1 parameter.
PROPERTY_L - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the L parameter.
PROPERTY_NEURONS - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The neurons property.
PROPERTY_PEAK - Static variable in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: The peak.
PROPERTY_RBF - Static variable in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: XML tag for the radial functions collection.
PROPERTY_RUN_CYCLES - Static variable in class org.encog.neural.networks.logic.BoltzmannLogic: Neural network property, the number of cycles to run.
PROPERTY_TEMPERATURE - Static variable in class org.encog.neural.networks.logic.BoltzmannLogic: Neural network property, the temperature.
PROPERTY_THRESHOLD - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The bias property, stores the bias weights.
PROPERTY_VIGILANCE - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the vigilance parameter.
PROPERTY_WIDTH - Static variable in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: The width.
PROPERTY_X - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The x-coordinate to place this object at.
PROPERTY_Y - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The y-coordinate to place this object at.
PropertyData - Class in org.encog.neural.data: An Encog data object that can be used to hold property data.
PropertyData() - Constructor for class org.encog.neural.data.PropertyData
PropertyDataPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the PropertyData class.
PropertyDataPersistor() - Constructor for class org.encog.persist.persistors.PropertyDataPersistor
prune(Layer, int) - Method in class org.encog.neural.prune.PruneSelective: Prune one of the neurons from this layer.
PruneIncremental - Class in org.encog.neural.prune: This class is used to help determine the optimal configuration for the hidden layers of a neural network.
PruneIncremental(NeuralDataSet, NeuralNetworkPattern, int, int, int, StatusReportable) - Constructor for class org.encog.neural.prune.PruneIncremental: Construct an object to determine the optimal number of hidden layers and neurons for the specified training data and pattern.
PruneSelective - Class in org.encog.neural.prune: Prune a neural network selectively.
PruneSelective(BasicNetwork) - Constructor for class org.encog.neural.prune.PruneSelective: Construct an object prune the neural network.
purge() - Method in class org.encog.solve.genetic.species.BasicSpecies: Purge all members, increase age by one and count the number of generations with no improvement.
purge() - Method in interface org.encog.solve.genetic.species.Species: Purge old unsuccessful genomes.
put(String, double[]) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation: Save a list of doubles.
putArray(double[]) - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Convert an array of doubles to the current best network.
putArray(Double[]) - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Used to pass the putArray call on to the parent object.
putArray(UNIT_TYPE[]) - Method in class org.encog.solve.anneal.SimulatedAnnealing: Store the array.
pythag(double, double) - Static method in class org.encog.neural.networks.training.svd.SVD

Q

QRDecomposition - Class in org.encog.mathutil.matrices.decomposition: QR Decomposition.
QRDecomposition(Matrix) - Constructor for class org.encog.mathutil.matrices.decomposition.QRDecomposition: QR Decomposition, computed by Householder reflections.

R

rad2deg(double) - Static method in class org.encog.mathutil.EncogMath: Convert radians to degrees.
RadialBasisFunction - Interface in org.encog.engine.network.rbf: A multi-dimension RBF.
RadialBasisFunctionLayer - Class in org.encog.neural.networks.layers: This layer type makes use of several radial basis function to scale the output from this layer.
RadialBasisFunctionLayer() - Constructor for class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Default constructor, mainly so the workbench can easily create a default layer.
RadialBasisFunctionLayer(int) - Constructor for class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Construct a radial basis function layer.
RadialBasisFunctionLayerPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the RadialBasisFunctionLayer class.
RadialBasisFunctionLayerPersistor() - Constructor for class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor
RadialBasisPattern - Class in org.encog.neural.pattern: A radial basis function (RBF) network uses several radial basis functions to provide a more dynamic hidden layer activation function than many other types of neural network.
RadialBasisPattern() - Constructor for class org.encog.neural.pattern.RadialBasisPattern
RANDOM_LENGTH - Static variable in class org.encog.util.http.FormUtility: The length of random string to create for multipart.
randomInt(int, int) - Static method in class org.encog.mathutil.randomize.RangeRandomizer
randomize() - Method in class org.encog.engine.network.flat.FlatNetwork: Perform a simple randomization of the weights of the neural network between -1 and 1.
randomize(double, double) - Method in class org.encog.engine.network.flat.FlatNetwork: Perform a simple randomization of the weights of the neural network between the specified hi and lo.
randomize(BasicNetwork) - Method in class org.encog.mathutil.randomize.BasicRandomizer: Randomize the synapses and biases in the basic network based on an array, modify the array.
randomize(BasicNetwork, Synapse) - Method in class org.encog.mathutil.randomize.BasicRandomizer: Randomize a synapse, only randomize those connections that are actually connected.
randomize(double[]) - Method in class org.encog.mathutil.randomize.BasicRandomizer: Randomize the array based on an array, modify the array.
randomize(Double[]) - Method in class org.encog.mathutil.randomize.BasicRandomizer: Randomize the array based on an array, modify the array.
randomize(double[][]) - Method in class org.encog.mathutil.randomize.BasicRandomizer: Randomize the 2d array based on an array, modify the array.
randomize(Double[][]) - Method in class org.encog.mathutil.randomize.BasicRandomizer: Randomize the 2d array based on an array, modify the array.
randomize(Matrix) - Method in class org.encog.mathutil.randomize.BasicRandomizer: Randomize the matrix based on an array, modify the array.
randomize(double) - Method in class org.encog.mathutil.randomize.ConsistentRandomizer: Generate a random number based on the range specified in the constructor.
randomize(BasicNetwork) - Method in class org.encog.mathutil.randomize.ConsistentRandomizer: Randomize the network.
randomize(double) - Method in class org.encog.mathutil.randomize.ConstRandomizer: Generate a random number based on the range specified in the constructor.
randomize(double) - Method in class org.encog.mathutil.randomize.Distort: Distort the random number by the factor that was specified in the constructor.
randomize(BasicNetwork, Synapse) - Method in class org.encog.mathutil.randomize.FanInRandomizer: Randomize a synapse, only randomize those connections that are actually connected.
randomize(double) - Method in class org.encog.mathutil.randomize.FanInRandomizer: Starting with the specified number, randomize it to the degree specified by this randomizer.
randomize(double[]) - Method in class org.encog.mathutil.randomize.FanInRandomizer: Randomize the array based on an array, modify the array.
randomize(Double[]) - Method in class org.encog.mathutil.randomize.FanInRandomizer: Randomize the array based on an array, modify the array.
randomize(double[][]) - Method in class org.encog.mathutil.randomize.FanInRandomizer: Randomize the 2d array based on an array, modify the array.
randomize(Double[][]) - Method in class org.encog.mathutil.randomize.FanInRandomizer: Randomize the 2d array based on an array, modify the array.
randomize(Matrix) - Method in class org.encog.mathutil.randomize.FanInRandomizer: Randomize the matrix based on an array, modify the array.
randomize(double) - Method in class org.encog.mathutil.randomize.GaussianRandomizer: Generate a random number.
randomize(BasicNetwork) - Method in class org.encog.mathutil.randomize.NguyenWidrowRandomizer: The Nguyen-Widrow initialization algorithm is the following :
1.
randomize(BasicNetwork) - Method in interface org.encog.mathutil.randomize.Randomizer: Randomize the synapses and bias values in the basic network based on an array, modify the array.
randomize(double) - Method in interface org.encog.mathutil.randomize.Randomizer: Starting with the specified number, randomize it to the degree specified by this randomizer.
randomize(double[]) - Method in interface org.encog.mathutil.randomize.Randomizer: Randomize the array based on an array, modify the array.
randomize(Double[]) - Method in interface org.encog.mathutil.randomize.Randomizer: Randomize the array based on an array, modify the array.
randomize(double[][]) - Method in interface org.encog.mathutil.randomize.Randomizer: Randomize the 2d array based on an array, modify the array.
randomize(Double[][]) - Method in interface org.encog.mathutil.randomize.Randomizer: Randomize the 2d array based on an array, modify the array.
randomize(Matrix) - Method in interface org.encog.mathutil.randomize.Randomizer: Randomize the matrix based on an array, modify the array.
randomize(double, double) - Static method in class org.encog.mathutil.randomize.RangeRandomizer: Generate a random number in the specified range.
randomize(double) - Method in class org.encog.mathutil.randomize.RangeRandomizer: Generate a random number based on the range specified in the constructor.
randomize() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Randomize the weights and bias values.
randomize() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Call the owner's randomize method.
randomize() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Randomize the weight matrix.
Randomizer - Interface in org.encog.mathutil.randomize: Defines the interface for a class that is capable of randomizing the weights and bias values of a neural network.
randomizeRBFCentersAndWidths(int, double, double, RBFEnum) - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Set the RBF components to random values.
randomString() - Static method in class org.encog.util.http.FormUtility: Generate a random string, of a specified length.
RandomTrainingFactory - Class in org.encog.util.benchmark: Class used to generate random training sets.
range(double, double) - Method in class org.encog.mathutil.LinearCongruentialGenerator: Generate a random number in the specified range.
RangeRandomizer - Class in org.encog.mathutil.randomize: A randomizer that will create random weight and bias values that are between a specified range.
RangeRandomizer(double, double) - Constructor for class org.encog.mathutil.randomize.RangeRandomizer: Construct a range randomizer.
RangeSegregator - Class in org.encog.normalize.segregate: Range segregators are used to segregate data and include or exclude if it is within a certain range.
RangeSegregator() - Constructor for class org.encog.normalize.segregate.RangeSegregator: Default constructor for reflection.
RangeSegregator(InputField, boolean) - Constructor for class org.encog.normalize.segregate.RangeSegregator: Construct a range segregator.
rank() - Method in class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition: Effective numerical matrix rank
RBF - Static variable in class org.encog.mathutil.libsvm.svm_parameter
RBF_LAYER - Static variable in class org.encog.neural.pattern.RadialBasisPattern
RBFEnum - Enum in org.encog.mathutil.rbf: The implemented function types of the RBFs.
read(double[], double[]) - Method in class org.encog.neural.data.buffer.codec.ArrayDataCODEC: Read one record of data from an external source.
read(double[], double[]) - Method in class org.encog.neural.data.buffer.codec.CSVDataCODEC: Read one record of data from a CSV file.
read(double[], double[]) - Method in interface org.encog.neural.data.buffer.codec.DataSetCODEC: Read one record of data from an external source.
read(double[], double[]) - Method in class org.encog.neural.data.buffer.codec.ExcelCODEC: Read one record of data from an external source.
read(double[], double[]) - Method in class org.encog.neural.data.buffer.codec.NeuralDataSetCODEC: Read one record of data from an external source.
read(int, int) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Read a row and column.
read(int, double[]) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Read a double array at the specified record.
read(double[]) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Read an array of doubles.
read() - Method in class org.encog.neural.data.buffer.EncogEGBFile: Read a single double.
read() - Method in class org.encog.parse.PeekableInputStream: Read a single byte from the stream.
read() - Method in class org.encog.parse.tags.read.ReadTags: Read a single character from the HTML source, if this function returns zero(0) then you should call getTag to see what tag was found.
ReadCSV - Class in org.encog.util.csv: Read and parse CSV format files.
ReadCSV(InputStream, boolean, char) - Constructor for class org.encog.util.csv.ReadCSV: Construct a CSV reader from an input stream.
ReadCSV(InputStream, boolean, CSVFormat) - Constructor for class org.encog.util.csv.ReadCSV: Construct a CSV reader from an input stream.
ReadCSV(String, boolean, char) - Constructor for class org.encog.util.csv.ReadCSV: Construct a CSV reader from a filename.
ReadCSV(String, boolean, CSVFormat) - Constructor for class org.encog.util.csv.ReadCSV: Construct a CSV reader from a filename.
readHeader() - Method in class org.encog.persist.PersistReader: Obtain the Encog header from the file.
ReadHTML - Class in org.encog.parse.tags.read: This class is designed to parse HTML documents.
ReadHTML(InputStream) - Constructor for class org.encog.parse.tags.read.ReadHTML: Construct a HTML reader.
readIntToTag() - Method in class org.encog.parse.tags.read.ReadXML: Read an integer that is contained between the current position, and the next tag.
readNextTag(String) - Method in class org.encog.persist.PersistReader: Read until the next tag of the specified name.
readNextText(String) - Method in class org.encog.persist.PersistReader: Read all text until the specified ending tag is found.
readObject(String) - Method in class org.encog.persist.PersistReader: Read the specific object, search through the objects until its found.
readPropertyBlock() - Method in class org.encog.parse.tags.read.ReadXML: Read all property data until an end tag, which corrisponds to the current tag, is found.
readStream(InputStream) - Static method in class org.encog.util.file.Directory: Read the entire contents of a stream into a string.
ReadTags - Class in org.encog.parse.tags.read: Base class used to read tags.
ReadTags(InputStream) - Constructor for class org.encog.parse.tags.read.ReadTags: The constructor should be passed an InputStream that we will parse from.
readTextFile(String) - Static method in class org.encog.util.file.Directory: Read the entire contents of a stream into a string.
readTextToTag() - Method in class org.encog.parse.tags.read.ReadXML: Read all text between the current position and the next tag.
readToTag() - Method in class org.encog.parse.tags.read.ReadTags: Read until we reach the next tag.
readValue(String) - Method in class org.encog.persist.PersistReader: Read the value in a period delimited string.
ReadXML - Class in org.encog.parse.tags.read: This class is designed to read XML.
ReadXML(InputStream) - Constructor for class org.encog.parse.tags.read.ReadXML: Construct an XML reader.
ready() - Method in interface org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformer
ready() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
recur() - Method in class org.encog.neural.networks.layers.BasicLayer: Get the output from this layer when called in a recurrent manor.
recur() - Method in class org.encog.neural.networks.layers.ContextLayer: Called to get the output from this layer when called in a recurrent manor.
recur() - Method in interface org.encog.neural.networks.layers.Layer: Called on recurrent layers to provide recurrent output.
REFF_ID - Static variable in class org.encog.persist.persistors.generic.Object2XML
ReflectionUtil - Class in org.encog.util.obj: This class includes some utilities to be used with reflection.
registerError(Throwable) - Method in class org.encog.engine.concurrency.EngineConcurrency: Allows threads to register errors, these errors will be thrown by the main thread.
registerIndividualEngineFactory(IndividualEngineFactory) - Method in class org.encog.script.EncogScriptEngineFactory
release() - Method in class org.encog.engine.opencl.kernels.EncogKernel: Release this kernel.
release() - Method in class org.encog.engine.opencl.kernels.KernelNetworkCalc: Release the kernel and all buffers.
release() - Method in class org.encog.engine.opencl.kernels.KernelNetworkTrain: Release the kernel and all buffers.
releaseBuffer(cl_mem) - Method in class org.encog.engine.opencl.kernels.EncogKernel: Release a buffer.
remove() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet.BasicNeuralIterator: Removes are not supported.
remove() - Method in class org.encog.neural.data.buffer.BufferedDataSetIterator: Not supported.
remove() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet.CSVNeuralIterator: Removes are not supported.
remove() - Method in class org.encog.neural.data.folded.FoldedIterator
remove(String) - Method in class org.encog.neural.data.PropertyData: Remove the specified property.
remove() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet.SQLNeuralIterator: Removes are not supported.
remove() - Method in class org.encog.neural.data.union.UnionNeuralDataSet.UnionIterator: Not implemented.
remove() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet.XMLNeuralIterator: Remove this iterator.
REMOVE_NOT_SUPPORTED - Static variable in class org.encog.neural.data.sql.SQLNeuralDataSet: Error message: removes are not supported.
removeAdditional(BufferedNeuralDataSet) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Remove an additional dataset that was created.
renameTo(PersistenceLocation) - Method in class org.encog.persist.location.FilePersistence: Rename this file to a different location.
renameTo(PersistenceLocation) - Method in class org.encog.persist.location.InputStreamPersistence: Renames are not allowed on this type of location.
renameTo(PersistenceLocation) - Method in class org.encog.persist.location.OutputStreamPersistence: Renames are not allowed on this type of location.
renameTo(PersistenceLocation) - Method in interface org.encog.persist.location.PersistenceLocation: Attempt to rename this location.
renameTo(PersistenceLocation) - Method in class org.encog.persist.location.ResourcePersistence: Rename is not supported for resource persistence.
report(int, int, String) - Method in class org.encog.ConsoleStatusReportable: Simply display any status reports.
report(double[], double, Throwable) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Called by the worker threads to report the progress at each step.
report(int, int, String) - Method in interface org.encog.engine.StatusReportable: Report on current status.
report(int, int, String) - Method in class org.encog.NullStatusReportable: Simply ignore any status reports.
reportStatus(JobUnitContext, String) - Method in class org.encog.engine.concurrency.job.ConcurrentJob: Report the status for this job.
requestNextTask() - Method in class org.encog.engine.concurrency.job.ConcurrentJob: Request the next task to be processed.
requestNextTask() - Method in class org.encog.neural.prune.PruneIncremental: Request the next task.
RequiredImprovementStrategy - Class in org.encog.neural.networks.training.strategy: The reset strategy will reset the weights if the neural network fails to improve by the specified amount over a number of cycles.
RequiredImprovementStrategy(double, int) - Constructor for class org.encog.neural.networks.training.strategy.RequiredImprovementStrategy: Construct a reset strategy.
RequiredImprovementStrategy(double, double, int) - Constructor for class org.encog.neural.networks.training.strategy.RequiredImprovementStrategy: Construct a reset strategy.
RequiredImprovementStrategy(int) - Constructor for class org.encog.neural.networks.training.strategy.RequiredImprovementStrategy: Reset if there is not at least a 1% improvement for 5 cycles.
RequireTwoPass - Interface in org.encog.normalize.output: Interface flag that indicates that a field type requires two passes.
reset() - Method in class org.encog.engine.util.ErrorCalculation: Reset the error accumulation to zero.
reset() - Method in class org.encog.engine.util.Stopwatch: Reset the stop watch.
reset() - Method in class org.encog.neural.networks.BasicNetwork: Reset the weight matrix and the bias values.
reset() - Method in class org.encog.neural.networks.logic.ART1Logic: Reset the weight matrix back to starting values.
reset() - Method in interface org.encog.neural.networks.Network: Reset the weight matrix and the bias values.
reset() - Method in class org.encog.neural.networks.training.competitive.BestMatchingUnit: Reset the "worst distance" back to a minimum value.
resetAndKill() - Method in class org.encog.neural.networks.training.neat.NEATTraining: Reset for an iteration.
ResetStrategy - Class in org.encog.neural.networks.training.strategy: The reset strategy will reset the weights if the neural network fails to fall below a specified error by a specified number of cycles.
ResetStrategy(double, int) - Constructor for class org.encog.neural.networks.training.strategy.ResetStrategy: Construct a reset strategy.
ResilientPropagation - Class in org.encog.neural.networks.training.propagation.resilient: One problem with the backpropagation algorithm is that the magnitude of the partial derivative is usually too large or too small.
ResilientPropagation(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Construct a resilient training object.
ResilientPropagation(BasicNetwork, NeuralDataSet, OpenCLTrainingProfile) - Constructor for class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Construct an RPROP trainer, allows an OpenCL device to be specified.
ResilientPropagation(BasicNetwork, NeuralDataSet, OpenCLTrainingProfile, double, double) - Constructor for class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Construct a resilient training object, allow the training parameters to be specified.
resolve() - Method in class org.encog.persist.persistors.generic.ObjectMapper: Resolve all references and place the correct objects.
resolveEncogClass(String) - Static method in class org.encog.util.obj.ReflectionUtil: Resolve an encog class using its simple name.
resolveEnum(Field, String) - Static method in class org.encog.util.obj.ReflectionUtil: Resolve an enumeration.
ResourceLoader - Class in org.encog.engine.util: Used to load resources from the JAR file.
ResourcePersistence - Class in org.encog.persist.location: A location that allows Encog objects to be read from a resource.
ResourcePersistence(String) - Constructor for class org.encog.persist.location.ResourcePersistence: Construct a location to read from the specified resource.
resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation: Resume training.
resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.Propagation: Resume training.
resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Resume training.
RGBDownsample - Class in org.encog.util.downsample: Downsample an image keeping the RGB colors.
RGBDownsample() - Constructor for class org.encog.util.downsample.RGBDownsample
rho - Variable in class org.encog.mathutil.libsvm.svm_model
rollIndex() - Method in class org.encog.normalize.segregate.index.IndexSegregator: Used to increase the current index as data is processed.
ROW - Static variable in class org.encog.persist.persistors.PersistorUtil: A matrix row.
rowInit() - Method in class org.encog.normalize.output.mapped.OutputFieldEncode: Not needed for this sort of output field.
rowInit() - Method in class org.encog.normalize.output.multiplicative.MultiplicativeGroup: Called to init this group for a new field.
rowInit() - Method in class org.encog.normalize.output.multiplicative.OutputFieldMultiplicative: Not needed for this sort of output field.
rowInit() - Method in class org.encog.normalize.output.nominal.OutputEquilateral: Determine which item's index is the value.
rowInit() - Method in class org.encog.normalize.output.nominal.OutputOneOf: Not needed for this sort of output field.
rowInit() - Method in interface org.encog.normalize.output.OutputField: Init this field for a new row.
rowInit() - Method in class org.encog.normalize.output.OutputFieldDirect: Not needed for this sort of output field.
rowInit() - Method in interface org.encog.normalize.output.OutputFieldGroup: Init the group for a new row.
rowInit() - Method in class org.encog.normalize.output.OutputFieldRangeMapped: Not needed for this sort of output field.
rowInit() - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxis: Not needed for this sort of output field.
rowInit() - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxisSynthetic: Not needed for this sort of output field.
rowInit() - Method in class org.encog.normalize.output.zaxis.ZAxisGroup: Initialize this group for a new row.
RPROPConst - Class in org.encog.engine.network.train.prop: Constants used for Resilient Propagation (RPROP) training.
RPROPJob - Class in org.encog.neural.networks.training.concurrent.jobs: A training definition for RPROP training.
RPROPJob(BasicNetwork, NeuralDataSet, boolean) - Constructor for class org.encog.neural.networks.training.concurrent.jobs.RPROPJob: Construct an RPROP job.
RPROPJob(BasicNetwork, NeuralDataSet, boolean, double, int, double, int) - Constructor for class org.encog.neural.networks.training.concurrent.jobs.RPROPJob: Construct an RPROP job.
RPROPJob(BasicNetwork, NeuralDataSet, boolean, double, double, double, int, double, int) - Constructor for class org.encog.neural.networks.training.concurrent.jobs.RPROPJob: Construct an RPROP job.
RSOMPattern - Class in org.encog.neural.pattern: A recurrent self organizing map is a self organizing map that has a recurrent context connection on the hidden layer.
RSOMPattern() - Constructor for class org.encog.neural.pattern.RSOMPattern
RSS - Class in org.encog.bot.rss: This is the class that actually parses the RSS and builds a collection of RSSItems.
RSS() - Constructor for class org.encog.bot.rss.RSS
RSSItem - Class in org.encog.bot.rss: This is the class that holds individual RSS items, or stories, for the RSS class.
RSSItem() - Constructor for class org.encog.bot.rss.RSSItem
run() - Method in class org.encog.cloud.AsynchronousCloudRequest: Ran by the thread to perform the request.
run() - Method in interface org.encog.engine.concurrency.EngineTask: The task to perform.
run() - Method in class org.encog.engine.concurrency.job.JobUnitWorker: Run this job unit.
run() - Method in class org.encog.engine.concurrency.PoolItem: Run the task.
run() - Method in class org.encog.engine.network.train.gradient.GradientWorkerCPU: Perform the gradient calculation for the specified index range.
run() - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Run the network for all neurons present.
run() - Method in class org.encog.neural.networks.logic.HopfieldLogic: Perform one Hopfield iteration.
run() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Perform the training.
run() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
run() - Method in class org.encog.neural.networks.training.concurrent.performers.PerformerTask
run(ConsoleInputOutput) - Method in class org.encog.script.EncogScript
run(EncogScript) - Method in interface org.encog.script.EncogScriptEngine
run() - Method in class org.encog.solve.genetic.MateWorker: Mate the two chromosomes.
runUntilStable(int) - Method in class org.encog.neural.networks.logic.HopfieldLogic: Run the network until it becomes stable and does not change from more runs.

S

safeHashCode(T) - Static method in class org.encog.util.obj.ReflectionUtil: Generate a hash code for an object.
save(PersistenceLocation) - Method in class org.encog.persist.EncogMemoryCollection: Save the contents of this collection to a location.
save(EncogPersistedObject, WriteXML) - Method in interface org.encog.persist.Persistor: Save the specified object.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.BasicLayerPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.BasicNetworkPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.BasicNeuralDataSetPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.BufferedNeuralDataSetPersistor: Save the binary file.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ContextLayerPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.DirectSynapsePersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.EncogScriptPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.generic.GenericPersistor: Save the specified object.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.generic.Object2XML: Save the object to XML.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.OneToOneSynapsePersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.PropertyDataPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: Save a RBF layer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.SVMNetworkPersistor: Save a SVMNetwork.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.TextDataPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.TrainingContinuationPersistor: Save the object.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.WeightedSynapsePersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.WeightlessSynapsePersistor: Save the specified Encog object to an XML writer.
save(String, Serializable) - Static method in class org.encog.util.obj.SerializeObject: Save the specified object.
saveActivationFunction(ActivationFunction, WriteXML) - Static method in class org.encog.persist.persistors.BasicLayerPersistor
saveCookies(URLConnection) - Method in class org.encog.util.http.CookieUtility: Once you have loaded cookies with loadCookies, you can call saveCookies to copy these cookies to a new HTTP request.
saveItems(WriteXML) - Method in class org.encog.persist.persistors.TrainingContinuationPersistor: Save items.
saveMatrix(Matrix, WriteXML) - Static method in class org.encog.persist.persistors.PersistorUtil: Save the specified matrix.
saveModel(WriteXML, svm_model) - Static method in class org.encog.persist.persistors.SVMNetworkPersistor: Save a model.
saveModified(WriteXML, String, String, String) - Method in class org.encog.persist.PersistReader: Modify the properties of this object.
saveTo(WriteXML, String) - Method in class org.encog.persist.PersistReader: Save all objects to the specified steam, skip the one specified by the skip parameter.
SCALE_LAMBDA - Static variable in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining: The amount to scale the lambda by.
ScaledConjugateGradient - Class in org.encog.neural.networks.training.propagation.scg: This is a training class that makes use of scaled conjugate gradient methods.
ScaledConjugateGradient(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient: Construct a training class.
scan(File) - Method in class org.encog.util.obj.GenerateClasslist: Scan the specified directory.
search(String) - Method in class org.encog.util.YahooSearch: Called to extract a list from the specified URL.
SECONDS_INA_DAY - Static variable in class org.encog.engine.util.Format: Seconds in a day.
SECONDS_INA_HOUR - Static variable in class org.encog.engine.util.Format: Seconds in an hour.
SECONDS_INA_MINUTE - Static variable in class org.encog.engine.util.Format: Seconds in a minute.
SECONDS_MINUTE - Static variable in class org.encog.util.time.TimeSpan: Seconds in a minute.
SegregationRange - Class in org.encog.normalize.segregate: Specifies a range that might be included or excluded.
SegregationRange() - Constructor for class org.encog.normalize.segregate.SegregationRange: Default constructor for reflection.
SegregationRange(double, double, boolean) - Constructor for class org.encog.normalize.segregate.SegregationRange: Construct a segregation range.
Segregator - Interface in org.encog.normalize.segregate: Segregators are used to exclude certain rows.
SerializeObject - Class in org.encog.util.obj: Load or save an object using Java serialization.
set(double) - Method in class org.encog.mathutil.matrices.Matrix: Set every value in the matrix to the specified value.
set(int, int, double) - Method in class org.encog.mathutil.matrices.Matrix: Set an individual cell in the matrix to the specified value.
set(Matrix) - Method in class org.encog.mathutil.matrices.Matrix: Set this matrix's values to that of another matrix.
set(String, String) - Method in class org.encog.neural.data.PropertyData: Set the specified property.
set(String, Object) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation: Set a value to a string.
setA1(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the A1 parameter.
setA1(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the A1 parameter.
setAction(Address) - Method in class org.encog.bot.browse.range.Form: Set the action for the form.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the activation function for this layer.
setActivationFunction(ActivationFunction) - Method in interface org.encog.neural.networks.layers.Layer: Set a new activation function for this layer.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Set the activation function.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.ADALINEPattern: Not used, ADALINE does not use custom activation functions.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.ART1Pattern: This method will throw an error, you can't set the activation function for an ART1.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.BAMPattern: Not used, the BAM uses a bipoloar activation function.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.BoltzmannPattern: Not used, will throw an exception.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.CPNPattern: This method will throw an error.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.ElmanPattern: Set the activation function to use on each of the layers.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.FeedForwardPattern: Set the activation function to use on each of the layers.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.HopfieldPattern: Set the activation function to use.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.JordanPattern: Set the activation function to use on each of the layers.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.NEATPattern: Set the activation function to use on the output layer.
setActivationFunction(ActivationFunction) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Set the activation function to be used for all created layers that allow an activation function to be specified.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.RadialBasisPattern: Set the activation function, this is an error.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.RSOMPattern: Set the activation function.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.SOMPattern: Set the activation function.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.SVMPattern: Not used, the BAM uses a bipoloar activation function.
setActivationResponse(double) - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene: Set the activation response.
setAdjustedScore(double) - Method in class org.encog.solve.genetic.genome.BasicGenome: Set the adjusted score.
setAdjustedScore(double) - Method in interface org.encog.solve.genetic.genome.Genome: Set the adjusted score.
setAge(int) - Method in class org.encog.solve.genetic.species.BasicSpecies: Set the age of this species.
setAge(int) - Method in interface org.encog.solve.genetic.species.Species: Set the age of this species.
setAmountToSpawn(double) - Method in class org.encog.solve.genetic.genome.BasicGenome: Set the amount to spawn.
setAmountToSpawn(double) - Method in interface org.encog.solve.genetic.genome.Genome: Set the amount to spawn.
setAnnealCycles(int) - Method in class org.encog.neural.pattern.BoltzmannPattern: Set the number of annealing cycles per run.
setArg(int, cl_mem) - Method in class org.encog.engine.opencl.kernels.EncogKernel: Set an argument.
setAttribute(String, String) - Method in class org.encog.parse.tags.Tag: Set a HTML attribute.
setAutoDecay(int, double, double, double, double) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Setup autodecay.
setB1(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the B1 parameter.
setB1(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the B1 parameter.
setBegin(int) - Method in class org.encog.bot.browse.range.DocumentRange: Set the beginning index.
setBeginTraining(int) - Method in class org.encog.engine.network.flat.FlatNetwork
setBestScore(double) - Method in class org.encog.solve.genetic.species.BasicSpecies: Set the best score.
setBestScore(double) - Method in interface org.encog.solve.genetic.species.Species: Set the best score.
setBiasActivation(double) - Method in class org.encog.neural.networks.BasicNetwork: Sets the bias activation for every layer that supports bias.
setBiasActivation(double) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the bias activation.
setBiasActivation(double) - Method in interface org.encog.neural.networks.layers.Layer: Most layer types will default this value to one.
setBiasWeight(int, double) - Method in class org.encog.neural.networks.layers.BasicLayer: Set an individual bias weight value.
setBiasWeight(int, double) - Method in class org.encog.neural.networks.layers.ContextLayer: Set a bias weight.
setBiasWeight(int, double) - Method in interface org.encog.neural.networks.layers.Layer: Set an individual bias weight value.
setBiasWeights(double[]) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the bias array.
setBiasWeights(double[]) - Method in class org.encog.neural.networks.layers.ContextLayer: Set the bias weights.
setBiasWeights(double[]) - Method in interface org.encog.neural.networks.layers.Layer: Set the bias weight array for this layer.
setC1(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the C1 parameter.
setC1(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the C1 parameter.
setCalculateScore(CalculateGenomeScore) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the score calculation object.
setCatchAll(double) - Method in class org.encog.normalize.output.mapped.OutputFieldEncode: Set the catch all value.
setCenter(double) - Method in class org.encog.engine.network.activation.ActivationStep: Set the center of this function.
setCenters(double[]) - Method in interface org.encog.engine.network.rbf.RadialBasisFunction: Set the centers.
setCenters(double[]) - Method in class org.encog.mathutil.rbf.BasicRBF: Set the centers.
setClassAttribute(String) - Method in class org.encog.bot.browse.range.DocumentRange
setCloseConnection(boolean) - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Allows you to determine if the connection should be closed.
setCloud(EncogCloud) - Method in class org.encog.neural.networks.training.BasicTraining: Set the cloud use to track this training.
setCloud(EncogCloud) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the Encog cloud to use.
setCloud(EncogCloud) - Method in interface org.encog.neural.networks.training.Train: Set the cloud use to track the training.
setCLSource(String) - Method in class org.encog.engine.opencl.kernels.EncogKernel
setCode(String) - Method in class org.encog.bot.dataunit.CodeDataUnit: Set the code to the specified string.
setCollection(EncogCollection) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Set the Encog collection that this object belongs to.
setCollection(EncogCollection) - Method in class org.encog.neural.networks.layers.BasicLayer: Not used, layers do not belong to collections.
setCollection(EncogCollection) - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse
setCollection(EncogCollection) - Method in class org.encog.persist.BasicPersistedObject
setCollection(EncogCollection) - Method in class org.encog.persist.BasicPersistedSubObject: Not implemented.
setCollection(EncogCollection) - Method in interface org.encog.persist.EncogPersistedObject
setCollection(EncogCollection) - Method in class org.encog.solve.genetic.population.BasicPopulation: Set the Encog collection that this object belongs to.
setComparator(GenomeComparator) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the comparator.
setConnectionLimit(double) - Method in class org.encog.engine.network.flat.FlatNetwork
setConsole(ConsoleInputOutput) - Method in interface org.encog.script.EncogScriptEngine
setConsoleLevel(Level) - Static method in class org.encog.util.logging.Logging: Set the logging level for console.
setConstBegin(double) - Method in class org.encog.neural.networks.training.svm.SVMTrain
setConstEnd(double) - Method in class org.encog.neural.networks.training.svm.SVMTrain
setConstStep(double) - Method in class org.encog.neural.networks.training.svm.SVMTrain
setContextFedBy(FlatLayer) - Method in class org.encog.engine.network.flat.FlatLayer: Set the layer that this layer's context is fed by.
setCrossover(Crossover) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the crossover object.
setCSVFormat(CSVFormat) - Method in class org.encog.normalize.DataNormalization: Set the CSV format to use.
setCurrentBlue(int) - Method in class org.encog.util.downsample.RGBDownsample: Set the current blue average.
setCurrentFold(int) - Method in class org.encog.neural.data.folded.FoldedDataSet: Set the current fold.
setCurrentGreen(int) - Method in class org.encog.util.downsample.RGBDownsample: Set the current green average.
setCurrentPage(WebPage) - Method in class org.encog.bot.browse.Browser: Set the current page.
setCurrentRed(int) - Method in class org.encog.util.downsample.RGBDownsample: Set the current red average.
setCurrentState(BiPolarNeuralData) - Method in class org.encog.neural.networks.logic.ThermalLogic
setCurrentValue(double) - Method in class org.encog.normalize.input.BasicInputField: Set the current value of this field.
setCurrentValue(double) - Method in interface org.encog.normalize.input.InputField: Set the current value of this field.
setCycles(int) - Method in class org.encog.solve.anneal.SimulatedAnnealing
setD1(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the D1 parameter.
setD1(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the D1 parameter.
setData(List<EngineData>) - Method in class org.encog.engine.data.BasicEngineDataSet
setData(double[]) - Method in class org.encog.neural.data.basic.BasicNeuralData: Set the entire data array.
setData(int, double) - Method in class org.encog.neural.data.basic.BasicNeuralData: Set the data element specified by the index.
setData(List<NeuralDataPair>) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
setData(double[]) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Store the array.
setData(int, boolean) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Set the specified index of this object as a boolean.
setData(int, double) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Set the specified index of this object as a double.
setData(MarketDataType, double) - Method in class org.encog.neural.data.market.loader.LoadedMarketData: Set financial data for this date.
setData(double[]) - Method in interface org.encog.neural.data.NeuralData: Set all of the data as an array of doubles.
setData(int, double) - Method in interface org.encog.neural.data.NeuralData: Set the specified element.
setData(double[]) - Method in class org.encog.neural.data.temporal.TemporalPoint
setData(int, double) - Method in class org.encog.neural.data.temporal.TemporalPoint: Set the data at the specified index.
setDate(Date) - Method in class org.encog.bot.rss.RSSItem: Set the publication date.
setDescription(String) - Method in class org.encog.bot.rss.RSSItem: Get the description.
setDescription(String) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
setDescription(String) - Method in class org.encog.neural.networks.layers.BasicLayer
setDescription(String) - Method in interface org.encog.neural.networks.Network: Set the description for this object.
setDescription(String) - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Not used.
setDescription(String) - Method in class org.encog.persist.BasicPersistedObject: Set the description of this object.
setDescription(String) - Method in class org.encog.persist.BasicPersistedSubObject: Not implemented.
setDescription(String) - Method in interface org.encog.persist.EncogPersistedObject: Set the description of this object.
setDescription(String) - Method in class org.encog.solve.genetic.population.BasicPopulation: Set the description.
setDesiredSetSize(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setDevice(EncogCLDevice) - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile: Set the device to use.
setDevice(EncogCLDevice) - Method in class org.encog.util.benchmark.EncogBenchmark
setEnabled(boolean) - Method in class org.encog.engine.opencl.EncogCLItem: Enable or disable this device or platform.
setEnabled(boolean) - Method in class org.encog.solve.genetic.genes.BasicGene
setEnabled(boolean) - Method in interface org.encog.solve.genetic.genes.Gene: Determine if this gene is enabled.
setEnd(int) - Method in class org.encog.bot.browse.range.DocumentRange: Set the ending index.
setEndTraining(int) - Method in class org.encog.engine.network.flat.FlatNetwork
setError(double) - Method in class org.encog.engine.concurrency.calc.CalculationResult
setError(double) - Method in class org.encog.neural.networks.training.BasicTraining
setError(Throwable) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
setError(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Not used.
setError(double) - Method in interface org.encog.neural.networks.training.Train
setError(double) - Method in class org.encog.util.simple.TrainingDialog: Set the current error.
setF1Neurons(int) - Method in class org.encog.neural.pattern.BAMPattern: Set the F1 neurons.
setF2Neurons(int) - Method in class org.encog.neural.pattern.BAMPattern: Set the output neurons.
setFlat(FlatNetwork) - Method in class org.encog.engine.opencl.kernels.KernelNetworkCalc
setFlatContextIndex(int) - Method in class org.encog.neural.networks.layers.ContextLayer: Set the flat context index.
setFlatTraining(TrainFlatNetwork) - Method in class org.encog.neural.networks.training.propagation.Propagation
setFlatUpdate(FlatUpdateNeeded) - Method in class org.encog.neural.networks.structure.NeuralStructure: Set the type of flat update needed.
setFold(int) - Method in class org.encog.neural.networks.training.svm.SVMTrain
setForceWinner(boolean) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Determine if a winner is to be forced.
setFrom(NeuralData) - Method in class org.encog.neural.networks.NeuralDataMapping: Set the from data.
setFromLayer(Layer) - Method in class org.encog.neural.networks.synapse.BasicSynapse: Set the from layer for this synapse.
setFromLayer(Layer) - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Set the from layer for this synapse.
setFromLayer(Layer) - Method in interface org.encog.neural.networks.synapse.Synapse: Set the from layer for this synapse.
setGammaBegin(double) - Method in class org.encog.neural.networks.training.svm.SVMTrain
setGammaEnd(double) - Method in class org.encog.neural.networks.training.svm.SVMTrain
setGammaStep(double) - Method in class org.encog.neural.networks.training.svm.SVMTrain
setGenetic(NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper) - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm: Set the genetic helper class.
setGeneticAlgorithm(GeneticAlgorithm) - Method in class org.encog.solve.genetic.genome.BasicGenome: Set the genetic algorithm to use.
setGenomeID(long) - Method in class org.encog.solve.genetic.genome.BasicGenome: Set the genome id.
setGenomeID(long) - Method in interface org.encog.solve.genetic.genome.Genome: Set the genome ID.
setGensNoImprovement(int) - Method in class org.encog.solve.genetic.species.BasicSpecies: Set the number of generations with no improvement.
setGensNoImprovement(int) - Method in interface org.encog.solve.genetic.species.Species: Set the number of generations with no improvement.
setGlobalRatio(int) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
setGlobalWork(int) - Method in class org.encog.engine.opencl.kernels.EncogKernel: Set the size of the global work group.
setHigh(double) - Method in class org.encog.engine.network.activation.ActivationRamp: Set the high value.
setHigh(double) - Method in class org.encog.engine.network.activation.ActivationStep: Set the high of this function.
setHigh(int) - Method in class org.encog.engine.util.IntRange: Set the high end of the range.
setHighSequence(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setID(int) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the id for this layer.
setID(int) - Method in interface org.encog.neural.networks.layers.Layer: Set the id for this layer.
setId(long) - Method in class org.encog.solve.genetic.genes.BasicGene: Set the id for this gene.
setIdAttribute(String) - Method in class org.encog.bot.browse.range.DocumentRange
setIdeal(boolean) - Method in class org.encog.normalize.output.BasicOutputField: Set if this is an ideal field.
setIdeal(boolean) - Method in interface org.encog.normalize.output.OutputField: Set whether this field is part of the ideal output for a network.
setIdealArray(double[]) - Method in class org.encog.engine.data.BasicEngineData: Set the ideal array.
setIdealArray(double[]) - Method in interface org.encog.engine.data.EngineData: Set the ideal data, the desired output.
setIdealArray(double[]) - Method in class org.encog.neural.data.basic.BasicNeuralDataPair
setImage(Image) - Method in class org.encog.neural.data.image.ImageNeuralData
setIndex(int) - Method in class org.encog.neural.data.temporal.TemporalDataDescription
setInitialUpdate(double) - Method in class org.encog.neural.networks.training.concurrent.jobs.RPROPJob
setInnovationId(long) - Method in class org.encog.solve.genetic.genes.BasicGene: Set the innovation id for this gene.
setInnovationID(long) - Method in class org.encog.solve.genetic.innovation.BasicInnovation: Set the innovation id.
setInnovationID(long) - Method in interface org.encog.solve.genetic.innovation.Innovation: Set the innovation id.
setInnovations(InnovationList) - Method in class org.encog.solve.genetic.population.BasicPopulation: Set the innovation list.
setInnovations(InnovationList) - Method in interface org.encog.solve.genetic.population.Population: Set the innovations collection.
setInputArray(double[]) - Method in class org.encog.engine.data.BasicEngineData: Set the input array.
setInputArray(double[]) - Method in interface org.encog.engine.data.EngineData: Set the input.
setInputArray(double[]) - Method in class org.encog.neural.data.basic.BasicNeuralDataPair
setInputNeurons(int) - Method in class org.encog.neural.pattern.ADALINEPattern: Set the input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.ART1Pattern: Set the input neuron (F1 layer) count.
setInputNeurons(int) - Method in class org.encog.neural.pattern.BAMPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.BoltzmannPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.CPNPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.ElmanPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.FeedForwardPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.HopfieldPattern: Set the number of input neurons, this must match the output neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.JordanPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.NEATPattern: Set the number of input neurons.
setInputNeurons(int) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.RadialBasisPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.RSOMPattern: Set the input neuron count.
setInputNeurons(int) - Method in class org.encog.neural.pattern.SOMPattern: Set the input neuron count.
setInputNeurons(int) - Method in class org.encog.neural.pattern.SVMPattern: Set the number of input neurons.
setInputWindowSize(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setInstarCount(int) - Method in class org.encog.neural.pattern.CPNPattern: Set the number of neurons in the instar layer.
setIteration(int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Set the iteration.
setIteration(int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Set the iteration.
setIteration(int) - Method in interface org.encog.engine.network.train.TrainFlatNetwork: Set the iteration.
setIteration(int) - Method in class org.encog.neural.networks.training.BasicTraining
setIteration(int) - Method in class org.encog.neural.networks.training.neat.NEATTraining
setIteration(int) - Method in interface org.encog.neural.networks.training.Train: Set the current training iteration.
setIterations(int) - Method in class org.encog.util.simple.TrainingDialog: Set the number of iterations.
setIterationsPer(int) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
setJobUnit(Object) - Method in class org.encog.engine.concurrency.job.JobUnitContext: Set the job unit.
setKernelType(KernelType) - Method in class org.encog.neural.pattern.SVMPattern
setL(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the L parameter.
setL(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the L parameter.
setLanguage(String) - Method in class org.encog.script.EncogScript
setLastDelta(double[]) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkBackPropagation: Set the last delta.
setLeader(Genome) - Method in class org.encog.solve.genetic.species.BasicSpecies: Set the leader.
setLeader(Genome) - Method in interface org.encog.solve.genetic.species.Species: Set the leader of this species.
setLearningRate(double) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkBackPropagation: Set the learning rate.
setLearningRate(double) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkManhattan
setLearningRate(double) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Set the learning rate.
setLearningRate(double) - Method in class org.encog.neural.networks.training.concurrent.jobs.BPROPJob
setLearningRate(double) - Method in class org.encog.neural.networks.training.cpn.TrainInstar: Set the learning rate.
setLearningRate(double) - Method in class org.encog.neural.networks.training.cpn.TrainOutstar: Set the learning rate.
setLearningRate(double) - Method in class org.encog.neural.networks.training.hebbian.HebbianTraining: Set the learning date.
setLearningRate(double) - Method in interface org.encog.neural.networks.training.LearningRate: Set the learning rate.
setLearningRate(double) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation: Set the learning rate, this is value is essentially a percent.
setLearningRate(double) - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation: Set the learning rate.
setLearningRate(double) - Method in class org.encog.neural.networks.training.simple.TrainAdaline: Set the learning rate.
setLink(String) - Method in class org.encog.bot.rss.RSSItem: Set the hyperlink.
setLoadToMemory(boolean) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
setLocalRatio(double) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
setLocalWork(int) - Method in class org.encog.engine.opencl.kernels.EncogKernel: Set the size of the local work group.
setLocation(int) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Set the current location to the specified row.
setLogic(NeuralLogic) - Method in class org.encog.neural.networks.BasicNetwork: Set the type of logic this network should use.
setLow(double) - Method in class org.encog.engine.network.activation.ActivationRamp: Set the low value.
setLow(double) - Method in class org.encog.engine.network.activation.ActivationStep: Set the low of this function.
setLow(int) - Method in class org.encog.engine.util.IntRange: Set the low end of the range.
setLowSequence(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setManager(ConcurrentTrainingManager) - Method in interface org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformer: Set the manager.
setManager(ConcurrentTrainingManager) - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU: Set the manager.
setMatingPopulation(double) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the mating population percent.
setMatrix(int, int, int, int, Matrix) - Method in class org.encog.mathutil.matrices.Matrix: Set a submatrix.
setMatrix(int, int, int[], Matrix) - Method in class org.encog.mathutil.matrices.Matrix: Set a submatrix.
setMatrix(int[], int, int, Matrix) - Method in class org.encog.mathutil.matrices.Matrix: Set a submatrix.
setMatrix(int[], int[], Matrix) - Method in class org.encog.mathutil.matrices.Matrix: Set a submatrix.
setMatrix(Matrix) - Method in class org.encog.neural.networks.synapse.DirectSynapse: Attempt to set the matrix for this layer.
setMatrix(Matrix) - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Assign a new weight matrix to this layer.
setMatrix(Matrix) - Method in class org.encog.neural.networks.synapse.OneToOneSynapse: Attempt to set the matrix for this layer.
setMatrix(Matrix) - Method in interface org.encog.neural.networks.synapse.Synapse: Assign a new weight matrix to this layer.
setMatrix(Matrix) - Method in class org.encog.neural.networks.synapse.WeightedSynapse: Assign a new weight matrix to this layer.
setMatrix(Matrix) - Method in class org.encog.neural.networks.synapse.WeightlessSynapse: Attempt to set the matrix for this layer.
setMax(double) - Method in class org.encog.normalize.input.BasicInputField: Set the current max value.
setMax(double) - Method in interface org.encog.normalize.input.InputField: Set the current max value.
setMaxStep(double) - Method in class org.encog.neural.networks.training.concurrent.jobs.RPROPJob
setMethod(Form.Method) - Method in class org.encog.bot.browse.range.Form: Set the method to send the form.
setMin(double) - Method in class org.encog.normalize.input.BasicInputField: Set the current min value.
setMin(double) - Method in interface org.encog.normalize.input.InputField: Set the current min value.
setMode(ErrorCalculationMode) - Static method in class org.encog.engine.util.ErrorCalculation: Set the error calculation mode, this is static and therefore global to all Enocg training.
setMomentum(double) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkBackPropagation: Set the momentum.
setMomentum(double) - Method in class org.encog.neural.networks.training.concurrent.jobs.BPROPJob
setMomentum(double) - Method in interface org.encog.neural.networks.training.Momentum: Set the momentum.
setMomentum(double) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation: Set the momentum for training.
setMutate(Mutate) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the mutate object.
setMutationPercent(double) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the mutation percent.
setName(String) - Method in class org.encog.bot.browse.range.FormElement: Set the name of this form element.
setName(String) - Method in class org.encog.engine.opencl.EncogCLItem: Set the name of this platform or device.
setName(String) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
setName(String) - Method in class org.encog.neural.networks.layers.BasicLayer
setName(String) - Method in interface org.encog.neural.networks.Network
setName(String) - Method in class org.encog.neural.networks.synapse.BasicSynapse: The EncogPersistedObject requires a name and description, however, these are not used on synapses.
setName(String) - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Not used.
setName(String) - Method in class org.encog.parse.tags.Tag: Set the tag name.
setName(String) - Method in class org.encog.persist.BasicPersistedObject: Set the name of this object.
setName(String) - Method in class org.encog.persist.BasicPersistedSubObject: Not implemented.
setName(String) - Method in interface org.encog.persist.EncogPersistedObject: Set the name of this object.
setName(String) - Method in class org.encog.solve.genetic.population.BasicPopulation: Set the name.
setNeatActivationFunction(ActivationFunction) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the NEAT activation, used by the NEAT neurons.
setNEATActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.NEATPattern: Set the activation function to use on the NEAT neurons.
setNetwork(FlatNetwork) - Method in class org.encog.engine.concurrency.calc.CalcOpenCLDevice: Set the network that we will be using.
setNetwork(FlatNetwork) - Method in class org.encog.engine.concurrency.calc.ConcurrentCalculate: Set the current network.
setNetwork(BasicNetwork) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the network for this layer.
setNetwork(BasicNetwork) - Method in interface org.encog.neural.networks.layers.Layer: Set the network that this layer belongs to.
setNetwork(BasicNetwork) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
setNetworkDepth(int) - Method in class org.encog.neural.networks.training.neat.NEATGenome
setNeuronCount(int) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the neuron count.
setNeuronCount(int) - Method in interface org.encog.neural.networks.layers.Layer: Set the neuron count, this will NOT adjust the synapses or bias weights other code must do that.
setNeuronID(long) - Method in class org.encog.neural.networks.training.neat.NEATInnovation: Set the neuron id.
setNeuronType(NEATNeuronType) - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene: Set the neuron type.
setNumThreads(int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Set the number of threads to use.
setNumThreads(int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Set the number of threads to use.
setNumThreads(int) - Method in interface org.encog.engine.network.train.TrainFlatNetwork: Set the number of threads to use.
setNumThreads(int) - Method in class org.encog.neural.networks.training.propagation.Propagation: Set the number of threads.
setOffset(int) - Method in class org.encog.normalize.input.InputFieldEncogCollection
setOldAgePenalty(double) - Method in class org.encog.solve.genetic.population.BasicPopulation: Set the old age penalty.
setOldAgePenalty(double) - Method in interface org.encog.solve.genetic.population.Population: Set the old age penalty.
setOldAgeThreshold(int) - Method in class org.encog.solve.genetic.population.BasicPopulation: Set the threshold at which a genome is considered "old".
setOldAgeThreshold(int) - Method in interface org.encog.solve.genetic.population.Population: Set the age at which a genome is considered "old".
setOrganism(Object) - Method in class org.encog.solve.genetic.genome.BasicGenome: Set the organism.
setOutput(NeuralData) - Method in class org.encog.neural.networks.NeuralOutputHolder: Set the output.
setOutput(double) - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron: Set the output.
setOutputActivationFunction(ActivationFunction) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the activatoin function for the Encog output layer.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.ADALINEPattern: Set the output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.ART1Pattern: Set the output neuron (F2 layer) count.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.BAMPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.BoltzmannPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.CPNPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.ElmanPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.FeedForwardPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.HopfieldPattern: Set the number of output neurons, should not be used with a hopfield neural network, because the number of input neurons defines the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.JordanPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.NEATPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.RadialBasisPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.RSOMPattern: Set the output neuron count.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.SOMPattern: Set the output neuron count.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.SVMPattern: Set the number of output neurons.
setOutstarCount(int) - Method in class org.encog.neural.pattern.CPNPattern: Set the number of neurons in the outstar level, this level is mapped to the "output" level.
setOwner(Form) - Method in class org.encog.bot.browse.range.FormElement: Set the owner of this form element.
setOwner(ConcurrentJob) - Method in class org.encog.engine.concurrency.job.JobUnitContext: Set the job owner.
setOwner(BufferedNeuralDataSet) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Set the owner of this dataset.
setOwner(FoldedDataSet) - Method in class org.encog.neural.data.folded.FoldedDataSet
setPair(NeuralDataPair) - Method in class org.encog.normalize.input.NeuralDataFieldHolder: Set the pair.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationBiPolar: Set one of the params for this activation function.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationCompetitive: Set one of the params for this activation function.
setParam(int, double) - Method in interface org.encog.engine.network.activation.ActivationFunction: Set one of the params for this activation function.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationGaussian: Set one of the params for this activation function.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationLinear: Set one of the params for this activation function.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationLOG: Set one of the params for this activation function.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationRamp: Set one of the params for this activation function.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationSigmoid: Set one of the params for this activation function.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationSIN: Set one of the params for this activation function.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationSoftMax: Set one of the params for this activation function.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationStep: Set one of the params for this activation function.
setParam(int, double) - Method in class org.encog.engine.network.activation.ActivationTANH: Set one of the params for this activation function.
setParamActivationMutationRate(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the activation mutation rate.
setParamChanceAddLink(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the chance to add a link.
setParamChanceAddNode(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the chance to add a node.
setParamChanceAddRecurrentLink(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the chance to add a recurrent link.
setParamCompatibilityThreshold(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the compatibility threshold for species.
setParamCrossoverRate(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the cross over rate.
setParamMaxActivationPerturbation(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the max activation perturbation.
setParamMaxNumberOfSpecies(int) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the maximum number of species.
setParamMaxPermittedNeurons(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the max permitted neurons.
setParamMaxWeightPerturbation(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the max weight perturbation.
setParamMutationRate(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the mutation rate.
setParamNumAddLinkAttempts(int) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the number of attempts to add a link.
setParamNumGensAllowedNoImprovement(int) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the number of no-improvement generations allowed.
setParamNumTrysToFindLoopedLink(int) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the number of tries to create a looped link.
setParamNumTrysToFindOldLink(int) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the number of tries to try an old link.
setParamProbabilityWeightReplaced(double) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set the probability to replace a weight.
setParams(double, double) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Set the learning rate and radius.
setParent(DocumentRange) - Method in class org.encog.bot.browse.range.DocumentRange: Set the parent.
setPeak(double) - Method in interface org.encog.engine.network.rbf.RadialBasisFunction: Set the peak.
setPeak(double) - Method in class org.encog.mathutil.rbf.BasicRBF: Set the peak.
setPercentToMate(double) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the percent to mate.
setPixelMap(int[]) - Method in class org.encog.util.downsample.RGBDownsample: Set the pixel map.
setPopulation(Population) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the population.
setPopulationSize(int) - Method in class org.encog.solve.genetic.population.BasicPopulation: Set the population size.
setPopulationSize(int) - Method in interface org.encog.solve.genetic.population.Population: Set the max population size.
setPredictWindowSize(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setProperty(String, double) - Method in class org.encog.neural.networks.BasicNetwork: Set a property as a double.
setProperty(String, long) - Method in class org.encog.neural.networks.BasicNetwork: Set a property as a long.
setProperty(String, String) - Method in class org.encog.neural.networks.BasicNetwork: Set a property as a double.
setRadialBasisFunction(RadialBasisFunction[]) - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Set the array of radial basis functions.
setRadius(double) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodBubble: Set the radius.
setRadius(double) - Method in interface org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodFunction: Set the radius.
setRadius(double) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodRBF: Set the radius.
setRadius(double) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingle: Set the radius.
setRadius(double) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingleRBF: Set the radius.
setRandom(Random) - Method in class org.encog.mathutil.randomize.BasicRandomizer
setRBFCentersAndWidths(double[][], double[], RBFEnum) - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Array containing center position.
setRBFCentersAndWidthsEqualSpacing(double, double, RBFEnum, int, double, boolean) - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Equally spaces all hidden neurons within the n dimensional variable space.
setRBFFunction(int, RBFEnum, double[], double) - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Set an RBF function.
setRecurrent(boolean) - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene: Set if this is a recurrent neuron.
setRegression(boolean) - Method in class org.encog.neural.pattern.SVMPattern
setReport(StatusReportable) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Setup the object to report status to.
setReport(StatusReportable) - Method in class org.encog.normalize.DataNormalization: Set the object that this one is reporting to.
setResourceName(String) - Method in class org.encog.normalize.input.InputFieldEncogCollection
setResourceName(String) - Method in class org.encog.normalize.target.NormalizationStorageEncogCollection
setRunCycles(int) - Method in class org.encog.neural.pattern.BoltzmannPattern: Set the number of cycles per run.
setScore(double) - Method in class org.encog.solve.anneal.SimulatedAnnealing: Set the score.
setScore(double) - Method in class org.encog.solve.genetic.genome.BasicGenome: Set the score.
setScore(double) - Method in interface org.encog.solve.genetic.genome.Genome: Set the score.
setSeed(long) - Method in class org.encog.mathutil.LinearCongruentialGenerator: Set the seed value.
setSegmentationRatio(double) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
setSequence(int) - Method in class org.encog.neural.data.temporal.TemporalPoint
setSequenceGrandularity(TimeUnit) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setShouldMinimize(boolean) - Method in class org.encog.solve.anneal.SimulatedAnnealing: Should the score be minimized.
setSingleThreaded(boolean) - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
setSnapshot(boolean) - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Sets if snapshot is used.
setSnapshot(boolean) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Set if we are using snapshot mode.
setSnapshot(boolean) - Method in class org.encog.neural.pattern.NEATPattern
setSource(WebPage) - Method in class org.encog.bot.browse.range.DocumentRange: Set the source web page.
setSource(String) - Method in class org.encog.script.EncogScript
setSpawnsRequired(double) - Method in class org.encog.solve.genetic.species.BasicSpecies: Set the number of spawns required.
setSpawnsRequired(double) - Method in interface org.encog.solve.genetic.species.Species: Set the number of spawns required.
setSpeciesID(long) - Method in class org.encog.neural.networks.training.neat.NEATGenome: Set the species id.
setSplitX(double) - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene: Set the split x.
setSplitY(double) - Method in class org.encog.neural.networks.training.neat.NEATNeuronGene: Set the split y.
setStartingPoint(Date) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setStartTemperature(double) - Method in class org.encog.solve.anneal.SimulatedAnnealing
setStatus(String) - Method in class org.encog.cloud.CloudTask: Set the status for this task.
setStatus(StatusReportable) - Method in class org.encog.neural.data.buffer.BinaryDataLoader: Set the object that status is reported to.
setStopTemperature(double) - Method in class org.encog.solve.anneal.SimulatedAnnealing
setSurvivalRate(double) - Method in class org.encog.solve.genetic.population.BasicPopulation: Set the survival rate.
setSurvivalRate(double) - Method in interface org.encog.solve.genetic.population.Population: Set the survival rate.
setSVMType(SVMType) - Method in class org.encog.neural.pattern.SVMPattern
setTag(Tag) - Method in class org.encog.bot.dataunit.TagDataUnit: Set the tag that this data unit is based on.
setTarget(Address) - Method in class org.encog.bot.browse.range.Link: Set the target of this link.
setTarget(NormalizationStorage) - Method in class org.encog.normalize.DataNormalization: Determines where the normalized data will be sent.
setTaskNumber(int) - Method in class org.encog.engine.concurrency.job.JobUnitContext: Set the task number.
setTempDataArray(float[]) - Method in class org.encog.engine.opencl.kernels.KernelNetworkTrain
setTemperature(double) - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Set the network temperature.
setTemperature(double) - Method in class org.encog.neural.pattern.BoltzmannPattern: Set the temperature.
setTemperature(double) - Method in class org.encog.solve.anneal.SimulatedAnnealing
setText(String) - Method in class org.encog.bot.dataunit.TextDataUnit: Set the text for this data unit.
setText(String) - Method in class org.encog.neural.data.TextData: Set the text held by this object.
setThresholdHigh(double) - Method in class org.encog.engine.network.activation.ActivationRamp: Set the threshold high.
setThresholdLow(double) - Method in class org.encog.engine.network.activation.ActivationRamp: Set the threshold low.
setTime(int) - Method in class org.encog.util.simple.TrainingDialog: Set the time.
setTitle(DocumentRange) - Method in class org.encog.bot.browse.WebPage: Set the title of this document.
setTitle(String) - Method in class org.encog.bot.rss.RSSItem: Set the item title.
setTo(NeuralData) - Method in class org.encog.neural.networks.NeuralDataMapping: Set the target data.
setToLayer(Layer) - Method in class org.encog.neural.networks.synapse.BasicSynapse: Set the target layer from this synapse.
setToLayer(Layer) - Method in class org.encog.neural.networks.synapse.neat.NEATSynapse: Set the target layer from this synapse.
setToLayer(Layer) - Method in interface org.encog.neural.networks.synapse.Synapse: Set the target layer from this synapse.
setTrain(Train) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
setTraining(EngineIndexableSet) - Method in class org.encog.engine.concurrency.calc.CalcOpenCLDevice: Set the training data that will be used.
setTraining(EngineIndexableSet) - Method in class org.encog.engine.opencl.kernels.KernelNetworkCalc
setTraining(NeuralDataSet) - Method in class org.encog.neural.networks.training.BasicTraining: Set the training object that this strategy is working with.
setTraining(NeuralDataSet) - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
setTrainingData(EngineIndexableSet) - Method in class org.encog.engine.concurrency.calc.ConcurrentCalculate: Set the current training data.
setType(String) - Method in class org.encog.bot.browse.range.Input: Set the type of this input element.
setType(Tag.Type) - Method in class org.encog.parse.tags.Tag: Set the tag type.
setUseBayesianRegularization(boolean) - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining: Set if Bayesian regularization should be used.
setUsedForNetworkInput(boolean) - Method in class org.encog.normalize.input.BasicInputField: This is needed so that the buildForNetworkInput method of the normalization class knows how many input fields to expect.
setUseOpenCL(boolean) - Method in class org.encog.engine.concurrency.calc.ConcurrentCalculate
setValue(String) - Method in class org.encog.bot.browse.range.FormElement: Set the value for this form element.
setValue(char) - Method in class org.encog.solve.genetic.genes.CharGene: Set the value of this gene.
setValue(double) - Method in class org.encog.solve.genetic.genes.DoubleGene: Set the value of the gene.
setValue(int) - Method in class org.encog.solve.genetic.genes.IntegerGene: Set the value of this gene.
setVender(String) - Method in class org.encog.engine.opencl.EncogCLItem: Set the vender for this platform or device.
setVigilance(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the vigilance.
setVigilance(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the vigilance for the network.
setWeight(double) - Method in class org.encog.neural.networks.training.neat.NEATLinkGene: Set the weight of this connection.
setWidth(double) - Method in interface org.encog.engine.network.rbf.RadialBasisFunction: Set the width.
setWidth(double) - Method in class org.encog.mathutil.rbf.BasicRBF: Set the width.
setX(int) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the x coordinate for this layer.
setX(int) - Method in interface org.encog.neural.networks.layers.Layer: Set the x coordinate.
setY(int) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the y coordinate for this layer.
setY(int) - Method in interface org.encog.neural.networks.layers.Layer: Set the y coordinate.
setYoungBonusAgeThreshhold(int) - Method in class org.encog.solve.genetic.population.BasicPopulation: Set the young bonus age threshold.
setYoungBonusAgeThreshhold(int) - Method in interface org.encog.solve.genetic.population.Population: Set the age at which genoms are considered young.
setYoungScoreBonus(double) - Method in class org.encog.solve.genetic.population.BasicPopulation: Set the young genome bonus.
setYoungScoreBonus(double) - Method in interface org.encog.solve.genetic.population.Population: Set the youth score bonus.
shouldAccessField(Field, boolean) - Static method in class org.encog.util.obj.ReflectionUtil: Determine if Encog persistence should access the specified field.
shouldContinue() - Method in class org.encog.neural.networks.training.concurrent.jobs.TrainingJob
shouldInclude() - Method in class org.encog.normalize.segregate.index.IndexRangeSegregator: Determines if the current row should be included.
shouldInclude() - Method in class org.encog.normalize.segregate.index.IndexSampleSegregator: Should this row be included.
shouldInclude() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator: Determine of the current row should be included.
shouldInclude() - Method in class org.encog.normalize.segregate.RangeSegregator
shouldInclude() - Method in interface org.encog.normalize.segregate.Segregator: Should this row be included, according to this segregator.
shouldMinimize() - Method in interface org.encog.neural.networks.training.CalculateScore
shouldMinimize() - Method in class org.encog.neural.networks.training.genetic.GeneticScoreAdapter
shouldMinimize() - Method in class org.encog.neural.networks.training.TrainingSetScore: A training set based score should always seek to lower the error, as a result, this method always returns true.
shouldMinimize() - Method in interface org.encog.solve.genetic.genome.CalculateGenomeScore
shouldStop() - Method in class org.encog.neural.networks.training.strategy.end.EndIterationsStrategy
shouldStop() - Method in class org.encog.neural.networks.training.strategy.end.EndMaxErrorStrategy
shouldStop() - Method in class org.encog.neural.networks.training.strategy.end.EndMinutesStrategy
shouldStop() - Method in interface org.encog.neural.networks.training.strategy.end.EndTrainingStrategy
shouldStop() - Method in class org.encog.neural.networks.training.strategy.StopTrainingStrategy
shouldStop() - Method in class org.encog.util.simple.TrainingDialog
shrinking - Variable in class org.encog.mathutil.libsvm.svm_parameter
shutdown() - Method in class org.encog.Encog: Provides any shutdown that Encog may need.
shutdown(long) - Method in class org.encog.engine.concurrency.EngineConcurrency: Wait for all threads in the pool to complete.
shutdown() - Method in class org.encog.engine.EncogEngine: Provides any shutdown that Encog may need.
SIGMOID - Static variable in class org.encog.mathutil.libsvm.svm_parameter
SIGN(double, double) - Static method in class org.encog.neural.networks.training.svd.SVD
simpleFeedForward(int, int, int, int, boolean) - Static method in class org.encog.util.simple.EncogUtility: Create a simple feedforward neural network.
SimpleIntensityDownsample - Class in org.encog.util.downsample: Downsample an image using a simple intensity scale.
SimpleIntensityDownsample() - Constructor for class org.encog.util.downsample.SimpleIntensityDownsample
SimpleRecurrentLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for an Simple Recurrent Network (SRN) type network.
SimpleRecurrentLogic() - Constructor for class org.encog.neural.networks.logic.SimpleRecurrentLogic
SimulatedAnnealing<UNIT_TYPE> - Class in org.encog.solve.anneal: Simulated annealing is a common training method.
SimulatedAnnealing() - Constructor for class org.encog.solve.anneal.SimulatedAnnealing
sin(double) - Static method in class org.encog.engine.util.BoundMath: Calculate the sin.
singular(TimeUnit) - Method in class org.encog.util.time.EnglishTimeUnitNames: Get the singular form for a TimeUnit.
singular(TimeUnit) - Method in interface org.encog.util.time.TimeUnitNames: Get the singular form of the specified time unit.
SingularValueDecomposition - Class in org.encog.mathutil.matrices.decomposition: Singular Value Decomposition.
SingularValueDecomposition(Matrix) - Constructor for class org.encog.mathutil.matrices.decomposition.SingularValueDecomposition: Construct the singular value decomposition Structure to access U, S and V.
size() - Method in class org.encog.mathutil.matrices.Matrix: Get the size of the array.
size() - Method in class org.encog.neural.data.basic.BasicNeuralData: Get the number of data elements present.
size() - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Get the size of this data object.
size() - Method in interface org.encog.neural.data.NeuralData
size() - Method in class org.encog.neural.data.PropertyData
size() - Method in class org.encog.solve.genetic.genome.Chromosome
size() - Method in class org.encog.solve.genetic.population.BasicPopulation
size() - Method in interface org.encog.solve.genetic.population.Population
skip(long) - Method in class org.encog.parse.PeekableInputStream: Skip the specified number of bytes.
SmartLearningRate - Class in org.encog.neural.networks.training.strategy: Attempt to automatically set the learning rate in a learning method that supports a learning rate.
SmartLearningRate() - Constructor for class org.encog.neural.networks.training.strategy.SmartLearningRate
SmartMomentum - Class in org.encog.neural.networks.training.strategy: Attempt to automatically set a momentum in a training algorithm that supports momentum.
SmartMomentum() - Constructor for class org.encog.neural.networks.training.strategy.SmartMomentum
solve(Matrix) - Method in class org.encog.mathutil.matrices.decomposition.CholeskyDecomposition: Solve A*X = B.
solve(Matrix) - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition: Solve A*X = B
Solve(double[]) - Method in class org.encog.mathutil.matrices.decomposition.LUDecomposition
solve(Matrix) - Method in class org.encog.mathutil.matrices.decomposition.QRDecomposition: Least squares solution of A*X = B
solve(Matrix) - Method in class org.encog.mathutil.matrices.Matrix: Solve A*X = B.
SOMLogic - Class in org.encog.neural.networks.logic: Not really any different than the simple recurrent logic, but leaves for Encog SOM logic to be expanded in the future, and allows SOM specific trainers to exclude this logic type.
SOMLogic() - Constructor for class org.encog.neural.networks.logic.SOMLogic
SOMPattern - Class in org.encog.neural.pattern: A self organizing map is a neural network pattern with an input and output layer.
SOMPattern() - Constructor for class org.encog.neural.pattern.SOMPattern
sort() - Method in class org.encog.neural.networks.structure.NeuralStructure: Sort the layers and synapses.
sort() - Method in class org.encog.solve.genetic.population.BasicPopulation: Sort the population.
sort() - Method in interface org.encog.solve.genetic.population.Population: Sort the population by best score.
sortAndRecord() - Method in class org.encog.neural.networks.training.neat.NEATTraining: Sort the genomes.
sortGenes() - Method in class org.encog.neural.networks.training.neat.NEATGenome: Sort the genes.
sortPoints() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Sort the points.
Span - Class in org.encog.bot.browse.range: A document range that specifies a span tag, and any embedded tags.
Span(WebPage) - Constructor for class org.encog.bot.browse.range.Span: Construct a span range from the specified web page.
SPECIAL_CHAR_LIMIT - Static variable in class org.encog.util.http.URLUtility: Beyond this number are special chars.
speciateAndCalculateSpawnLevels() - Method in class org.encog.neural.networks.training.neat.NEATTraining: Determine the species.
Species - Interface in org.encog.solve.genetic.species: Defines the features used in a species.
Splice - Class in org.encog.solve.genetic.crossover: A simple cross over where genes are simply "spliced".
Splice(int) - Constructor for class org.encog.solve.genetic.crossover.Splice: Create a slice crossover with the specified cut length.
SpliceNoRepeat - Class in org.encog.solve.genetic.crossover: A simple cross over where genes are simply "spliced".
SpliceNoRepeat(int) - Constructor for class org.encog.solve.genetic.crossover.SpliceNoRepeat: Construct a splice crossover.
SQLNeuralDataSet - Class in org.encog.neural.data.sql: A dataset based on a SQL query.
SQLNeuralDataSet(Connection, String, int, int) - Constructor for class org.encog.neural.data.sql.SQLNeuralDataSet: Create a SQLNeuralDataSet based on the specified connection.
SQLNeuralDataSet(String, int, int, String, String, String, String) - Constructor for class org.encog.neural.data.sql.SQLNeuralDataSet: Construct a SQL dataset.
SQLNeuralDataSet.SQLNeuralIterator - Class in org.encog.neural.data.sql: Iterator used to iterate over SQL results.
SQLNeuralDataSet.SQLNeuralIterator() - Constructor for class org.encog.neural.data.sql.SQLNeuralDataSet.SQLNeuralIterator: Construct an iterator.
sqrt(double) - Static method in class org.encog.engine.util.BoundMath: Calculate the square root.
StandardConsole - Class in org.encog.script
StandardConsole() - Constructor for class org.encog.script.StandardConsole
start() - Method in class org.encog.engine.util.Stopwatch: Start the stop watch.
start() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Start the manager.
START_MOMENTUM - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum: The starting momentum.
START_X - Static variable in class org.encog.neural.pattern.PatternConst: The starting x-coordinate.
START_Y - Static variable in class org.encog.neural.pattern.PatternConst: The starting y-coordinate.
statIterations - Variable in class org.encog.mathutil.libsvm.svm_parameter
StatusReportable - Interface in org.encog.engine: This class allows for Encog jobs to report their current status, as they run.
stimulateNeuron(double, Layer, int) - Method in class org.encog.neural.prune.PruneSelective: Stimulate the specified neuron by the specified percent.
stimulateWeakNeurons(Layer, int, double) - Method in class org.encog.neural.prune.PruneSelective: Stimulate weaker neurons on a layer.
stop(String) - Method in class org.encog.cloud.CloudTask: Stop this task.
stop() - Method in class org.encog.engine.concurrency.job.ConcurrentJob: Request the process to stop.
stop() - Method in class org.encog.engine.util.Stopwatch: Stop the stopwatch.
stopConsoleLogging() - Static method in class org.encog.util.logging.Logging: Stop logging to the console.
StopTrainingStrategy - Class in org.encog.neural.networks.training.strategy: This strategy will indicate once training is no longer improving the neural network by a specified amount, over a specified number of cycles.
StopTrainingStrategy() - Constructor for class org.encog.neural.networks.training.strategy.StopTrainingStrategy: Construct the strategy with default options.
StopTrainingStrategy(double, int) - Constructor for class org.encog.neural.networks.training.strategy.StopTrainingStrategy: Construct the strategy with the specified parameters.
Stopwatch - Class in org.encog.engine.util: A stopwatch, meant to emulate the C# Stopwatch class.
Stopwatch() - Constructor for class org.encog.engine.util.Stopwatch: Construct a stopwatch.
Strategy - Interface in org.encog.neural.networks.training: Training strategies can be added to training algorithms.
string2double(String) - Static method in class org.encog.mathutil.Convert: Convert a string to a double.
string2int(String) - Static method in class org.encog.mathutil.Convert: Convert a string to an int.
stripTags(String) - Static method in class org.encog.bot.BotUtil: Strip any HTML or XML tags from the specified string.
subtract(Matrix, Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath: Return the results of subtracting one matrix from another.
sum() - Method in class org.encog.mathutil.matrices.Matrix: Sum all of the values in the matrix.
SV - Variable in class org.encog.mathutil.libsvm.svm_model
sv_coef - Variable in class org.encog.mathutil.libsvm.svm_model
SVD - Class in org.encog.neural.networks.training.svd: Perform a SVD decomp on a matrix.
SVD() - Constructor for class org.encog.neural.networks.training.svd.SVD
svdbksb(double[][], double[], double[][], double[][], double[][]) - Static method in class org.encog.neural.networks.training.svd.SVD
svdcmp(double[][], double[], double[][]) - Static method in class org.encog.neural.networks.training.svd.SVD
svdfit(double[][], double[][], double[][], RadialBasisFunction[]) - Static method in class org.encog.neural.networks.training.svd.SVD
SVDTraining - Class in org.encog.neural.networks.training.svd: Train a RBF neural network using a SVD.
SVDTraining(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.svd.SVDTraining: Construct the training object.
svm - Class in org.encog.mathutil.libsvm
svm() - Constructor for class org.encog.mathutil.libsvm.svm
svm_check_parameter(svm_problem, svm_parameter) - Static method in class org.encog.mathutil.libsvm.svm
svm_check_probability_model(svm_model) - Static method in class org.encog.mathutil.libsvm.svm
svm_cross_validation(svm_problem, svm_parameter, int, double[]) - Static method in class org.encog.mathutil.libsvm.svm
svm_get_labels(svm_model, int[]) - Static method in class org.encog.mathutil.libsvm.svm
svm_get_nr_class(svm_model) - Static method in class org.encog.mathutil.libsvm.svm
svm_get_svm_type(svm_model) - Static method in class org.encog.mathutil.libsvm.svm
svm_get_svr_probability(svm_model) - Static method in class org.encog.mathutil.libsvm.svm
svm_load_model(String) - Static method in class org.encog.mathutil.libsvm.svm
svm_load_model(BufferedReader) - Static method in class org.encog.mathutil.libsvm.svm
svm_model - Class in org.encog.mathutil.libsvm: This class was taken from the libsvm package.
svm_model() - Constructor for class org.encog.mathutil.libsvm.svm_model
svm_node - Class in org.encog.mathutil.libsvm: This class was taken from the libsvm package.
svm_node() - Constructor for class org.encog.mathutil.libsvm.svm_node
svm_parameter - Class in org.encog.mathutil.libsvm: This class was taken from the libsvm package.
svm_parameter() - Constructor for class org.encog.mathutil.libsvm.svm_parameter
svm_predict(svm_model, svm_node[]) - Static method in class org.encog.mathutil.libsvm.svm
svm_predict_probability(svm_model, svm_node[], double[]) - Static method in class org.encog.mathutil.libsvm.svm
svm_predict_values(svm_model, svm_node[], double[]) - Static method in class org.encog.mathutil.libsvm.svm
svm_print_interface - Interface in org.encog.mathutil.libsvm: This class was taken from the libsvm package.
svm_problem - Class in org.encog.mathutil.libsvm: This class was taken from the libsvm package.
svm_problem() - Constructor for class org.encog.mathutil.libsvm.svm_problem
svm_save_model(String, svm_model) - Static method in class org.encog.mathutil.libsvm.svm
svm_save_model(DataOutputStream, svm_model) - Static method in class org.encog.mathutil.libsvm.svm
svm_set_print_string_function(svm_print_interface) - Static method in class org.encog.mathutil.libsvm.svm
svm_train(svm_problem, svm_parameter) - Static method in class org.encog.mathutil.libsvm.svm
svm_type - Variable in class org.encog.mathutil.libsvm.svm_parameter
svm_type_table - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: Constants for the SVM types.
SVMNetwork - Class in org.encog.neural.networks.svm: This is a network that is backed by one or more Support Vector Machines (SVM).
SVMNetwork(int, int, SVMType, KernelType) - Constructor for class org.encog.neural.networks.svm.SVMNetwork: Construct a SVM network.
SVMNetwork(int, int, boolean) - Constructor for class org.encog.neural.networks.svm.SVMNetwork: Construct an SVM network.
SVMNetworkPersistor - Class in org.encog.persist.persistors: Persist a SVM network.
SVMNetworkPersistor() - Constructor for class org.encog.persist.persistors.SVMNetworkPersistor
SVMPattern - Class in org.encog.neural.pattern
SVMPattern() - Constructor for class org.encog.neural.pattern.SVMPattern
SVMTrain - Class in org.encog.neural.networks.training.svm: Provides training for Support Vector Machine networks.
SVMTrain(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.svm.SVMTrain: Construct a trainer for an SVM network.
SVMType - Enum in org.encog.neural.networks.svm: Supports both class and new support vector calculations, as well as one-class distribution.
Synapse - Interface in org.encog.neural.networks.synapse: A synapse is the connection between two layers of a neural network.
SynapseComparator - Class in org.encog.neural.networks.structure: Used to compare the order of synapses.
SynapseComparator(NeuralStructure) - Constructor for class org.encog.neural.networks.structure.SynapseComparator: Construct a layer comparator.
SynapseType - Enum in org.encog.neural.networks.synapse: Specifies the type of synapse to be created.

T

Tag - Class in org.encog.parse.tags: HTMLTag: This class holds a single HTML tag.
Tag() - Constructor for class org.encog.parse.tags.Tag
Tag.Type - Enum in org.encog.parse.tags: Tag types.
TAG_ACTIVATION - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The activation function tag.
TAG_COEF0 - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The coefficient.
TAG_DATA - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The data tag.
TAG_DEGREE - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The degree to use.
TAG_F1 - Static variable in class org.encog.neural.pattern.ART1Pattern: The tag for the F1 layer.
TAG_F1 - Static variable in class org.encog.neural.pattern.BAMPattern: The tag for the F1 layer.
TAG_F2 - Static variable in class org.encog.neural.pattern.ART1Pattern: The tag for the F2 layer.
TAG_F2 - Static variable in class org.encog.neural.pattern.BAMPattern: The tag for the F2 layer.
TAG_FILE - Static variable in class org.encog.persist.persistors.BufferedNeuralDataSetPersistor: Tag to hold the binary file name.
TAG_GAMMA - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The gamma to use.
TAG_IDEAL - Static variable in class org.encog.persist.persistors.BasicNeuralDataSetPersistor: THe ideal tag.
TAG_INPUT - Static variable in class org.encog.neural.networks.BasicNetwork: Tag used for the input layer.
TAG_INPUT - Static variable in class org.encog.persist.persistors.BasicNeuralDataSetPersistor: The input tag.
TAG_INPUT - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The input tag.
TAG_INSTAR - Static variable in class org.encog.neural.pattern.CPNPattern: The tag for the INSTAR layer.
TAG_ITEM - Static variable in class org.encog.persist.persistors.BasicNeuralDataSetPersistor: The item tag.
TAG_ITEM - Static variable in class org.encog.persist.persistors.TrainingContinuationPersistor: An item tag.
TAG_ITEMS - Static variable in class org.encog.persist.persistors.TrainingContinuationPersistor: The items tag.
TAG_LABEL - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The labels.
TAG_LAYER - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The layer synapse.
TAG_LAYERS - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The layers tag.
TAG_LIMIT - Static variable in class org.encog.neural.networks.BasicNetwork: Tag used for the connection limit.
TAG_LOGIC - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The logic tag.
TAG_MODEL - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The model tag.
TAG_MODELS - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The models tag.
TAG_NSV - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The number of support vectors.
TAG_NUMCLASS - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The number of classes.
TAG_OBJECTS - Static variable in class org.encog.persist.PersistReader: The objects tag.
TAG_OUTPUT - Static variable in class org.encog.neural.networks.BasicNetwork: Tag used for the output layer.
TAG_OUTPUT - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor
TAG_OUTPUT - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The output tag.
TAG_OUTSTAR - Static variable in class org.encog.neural.pattern.CPNPattern: The tag for the OUTSTAR layer.
TAG_PROB_A - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The A-probability.
TAG_PROB_B - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The B-probability.
TAG_PROPERTIES - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The properties tag.
TAG_PROPERTIES - Static variable in class org.encog.persist.persistors.PropertyDataPersistor: The properties tag.
TAG_PROPERTY - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The property tag.
TAG_PROPERTY - Static variable in class org.encog.persist.persistors.PropertyDataPersistor: The property tag.
TAG_RHO - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The rho to use.
TAG_ROW - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The row tag.
TAG_SOURCE - Static variable in class org.encog.persist.persistors.EncogScriptPersistor
TAG_SYNAPSE - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The synapse tag.
TAG_SYNAPSES - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The synapses tag.
TAG_TAG - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The tag tag.
TAG_TAGS - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The tags tag.
TAG_TOTALSV - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The total number of cases.
TAG_TYPE_KERNEL - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The type of kernel to use.
TAG_TYPE_SVM - Static variable in class org.encog.persist.persistors.SVMNetworkPersistor: The type of SVM this is.
TAG_WEIGHTS - Static variable in class org.encog.persist.persistors.WeightedSynapsePersistor: The weights tag.
TagConst - Class in org.encog.parse.tags: Constants to use while parsing the tags.
TagDataUnit - Class in org.encog.bot.dataunit: A data unit that holds a tag.
TagDataUnit() - Constructor for class org.encog.bot.dataunit.TagDataUnit
tagLayer(String, Layer) - Method in class org.encog.neural.networks.BasicNetwork: Tag a layer.
tanh(double) - Static method in class org.encog.engine.util.BoundMath: Calculate TANH, within bounds.
TaskGroup - Class in org.encog.engine.concurrency: A task group is a group of tasks that you would like to execute at once.
TaskGroup(int) - Constructor for class org.encog.engine.concurrency.TaskGroup: Create a task group with the specified id.
taskStarting() - Method in class org.encog.engine.concurrency.TaskGroup: Notify that a task is starting.
taskStopping() - Method in class org.encog.engine.concurrency.TaskGroup: Notify that a task is stopping.
TemporalDataDescription - Class in org.encog.neural.data.temporal: This class describes one unit of input, or output, to a temporal neural network.
TemporalDataDescription(ActivationFunction, double, double, TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.neural.data.temporal.TemporalDataDescription: Construct a data description item.
TemporalDataDescription(ActivationFunction, TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.neural.data.temporal.TemporalDataDescription: Construct a data description with an activation function, but no range.
TemporalDataDescription(TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.neural.data.temporal.TemporalDataDescription: Construct a data description with no activation function or range.
TemporalDataDescription.Type - Enum in org.encog.neural.data.temporal: The type of data requested.
TemporalError - Exception in org.encog.neural.data.temporal: Error occurred processing temporal data.
TemporalError(String) - Constructor for exception org.encog.neural.data.temporal.TemporalError: Construct a message exception.
TemporalError(Throwable) - Constructor for exception org.encog.neural.data.temporal.TemporalError: Construct an exception that holds another exception.
TemporalNeuralDataSet - Class in org.encog.neural.data.temporal: This class implements a temporal neural data set.
TemporalNeuralDataSet(int, int) - Constructor for class org.encog.neural.data.temporal.TemporalNeuralDataSet: Construct a dataset.
TemporalPoint - Class in org.encog.neural.data.temporal: A temporal point is all of the data captured at one point in time to be used for prediction.
TemporalPoint(int) - Constructor for class org.encog.neural.data.temporal.TemporalPoint: Construct a temporal point of the specified size.
TextData - Class in org.encog.neural.data: An Encog object that can hold text data.
TextData() - Constructor for class org.encog.neural.data.TextData
TextDataPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the TextData class.
TextDataPersistor() - Constructor for class org.encog.persist.persistors.TextDataPersistor
TextDataUnit - Class in org.encog.bot.dataunit: A data unit that holds text.
TextDataUnit() - Constructor for class org.encog.bot.dataunit.TextDataUnit
ThermalLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for thermal networks.
ThermalLogic() - Constructor for class org.encog.neural.networks.logic.ThermalLogic
throwError(String) - Static method in class org.encog.persist.EncogPersistedCollection: Throw and log an error.
TickerSymbol - Class in org.encog.neural.data.market: Holds a ticker symbol and exchange.
TickerSymbol(String) - Constructor for class org.encog.neural.data.market.TickerSymbol: Construct a ticker symbol with no exchange.
TickerSymbol(String, String) - Constructor for class org.encog.neural.data.market.TickerSymbol: Construct a ticker symbol with exchange.
TimeSpan - Class in org.encog.util.time: A timespan between two Dates.
TimeSpan(Date, Date) - Constructor for class org.encog.util.time.TimeSpan: Construct a time span.
TimeUnit - Enum in org.encog.util.time: Time units.
TimeUnitNames - Interface in org.encog.util.time: Get the name or code for a time unit.
toBinary(double) - Static method in class org.encog.mathutil.matrices.BiPolarUtil: Convert bipolar to binary.
toBiPolar(double) - Static method in class org.encog.mathutil.matrices.BiPolarUtil: Convert binary to bipolar.
toList(CSVFormat, StringBuilder, double[]) - Static method in class org.encog.util.csv.NumberList: Convert an array of doubles to a comma separated list.
toNormalizedBinary(double) - Static method in class org.encog.mathutil.matrices.BiPolarUtil: Convert to binary and normalize.
TOO_BIG - Static variable in class org.encog.engine.util.BoundNumbers: Too big of a number.
TOO_SMALL - Static variable in class org.encog.engine.util.BoundNumbers: Too small of a number.
toPackedArray() - Method in class org.encog.mathutil.matrices.Matrix: Convert the matrix into a packed array.
toString() - Method in class org.encog.bot.browse.Address
toString() - Method in class org.encog.bot.browse.range.Div
toString() - Method in class org.encog.bot.browse.range.DocumentRange
toString() - Method in class org.encog.bot.browse.range.Form
toString() - Method in class org.encog.bot.browse.range.Input
toString() - Method in class org.encog.bot.browse.range.Link
toString() - Method in class org.encog.bot.browse.range.Span
toString() - Method in class org.encog.bot.browse.WebPage
toString() - Method in class org.encog.bot.dataunit.CodeDataUnit
toString() - Method in class org.encog.bot.dataunit.TagDataUnit
toString() - Method in class org.encog.bot.dataunit.TextDataUnit
toString() - Method in class org.encog.bot.rss.RSS
toString() - Method in class org.encog.bot.rss.RSSItem
toString() - Method in class org.encog.engine.data.BasicEngineData
toString() - Method in class org.encog.engine.network.flat.FlatLayer
toString() - Method in class org.encog.engine.network.train.prop.OpenCLTrainingProfile
toString() - Method in class org.encog.engine.opencl.EncogCL
toString() - Method in class org.encog.engine.opencl.EncogCLDevice
toString() - Method in class org.encog.mathutil.matrices.Matrix
toString() - Method in class org.encog.mathutil.NumericRange
toString() - Method in class org.encog.neural.data.basic.BasicNeuralData
toString() - Method in class org.encog.neural.data.basic.BasicNeuralDataPair
toString() - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData
toString() - Method in class org.encog.neural.data.image.ImageNeuralData
toString() - Method in class org.encog.neural.data.temporal.TemporalPoint
toString() - Method in class org.encog.neural.networks.BasicNetwork
toString() - Method in class org.encog.neural.networks.layers.BasicLayer
toString() - Method in interface org.encog.neural.networks.Network
toString() - Method in class org.encog.neural.networks.structure.AnalyzeNetwork
toString() - Method in class org.encog.neural.networks.synapse.BasicSynapse
toString() - Method in class org.encog.neural.networks.synapse.neat.NEATNeuron
toString() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
toString() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager
toString() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerCPU
toString() - Method in class org.encog.neural.networks.training.concurrent.performers.ConcurrentTrainingPerformerOpenCL
toString() - Method in class org.encog.neural.networks.training.neat.NEATGenome
toString() - Method in class org.encog.neural.networks.training.neat.NEATInnovation
toString() - Method in class org.encog.neural.networks.training.neat.NEATLinkGene
toString() - Method in class org.encog.normalize.input.InputFieldEncogCollection
toString() - Method in class org.encog.normalize.output.OutputFieldDirect
toString() - Method in class org.encog.parse.tags.read.ReadTags
toString() - Method in class org.encog.parse.tags.Tag: Convert this tag back into string form, with the beginning < and ending >.
toString() - Method in class org.encog.persist.DirectoryEntry
toString() - Method in class org.encog.solve.genetic.genes.CharGene
toString() - Method in class org.encog.solve.genetic.genes.DoubleGene
toString() - Method in class org.encog.solve.genetic.genes.IntegerGene
toString() - Method in class org.encog.solve.genetic.genome.BasicGenome
tournamentSelection(int) - Method in class org.encog.neural.networks.training.neat.NEATTraining: Select a gene using a tournament.
trace(double[][]) - Static method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining: Return the sum of the diagonal.
train() - Method in class org.encog.neural.networks.training.svm.SVMTrain: Quickly train all outputs with a C of 1.0 and a gamma equal to 1/(num inputs).
train(int, double, double) - Method in class org.encog.neural.networks.training.svm.SVMTrain: Quickly train one output with the specified gamma and C.
train(double, double) - Method in class org.encog.neural.networks.training.svm.SVMTrain: Quickly train the network with a fixed gamma and C.
Train - Interface in org.encog.neural.networks.training: Interface for all neural network training methods.
TrainAdaline - Class in org.encog.neural.networks.training.simple: Train an ADALINE neural network.
TrainAdaline(BasicNetwork, NeuralDataSet, double) - Constructor for class org.encog.neural.networks.training.simple.TrainAdaline: Construct an ADALINE trainer.
trainConsole(BasicNetwork, NeuralDataSet, int) - Static method in class org.encog.util.simple.EncogUtility: Train the neural network, using SCG training, and output status to the console.
trainConsole(Train, BasicNetwork, NeuralDataSet, int) - Static method in class org.encog.util.simple.EncogUtility: Train the network, using the specified training algorithm, and send the output to the console.
trainDialog(BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.simple.EncogUtility: Train using SCG and display progress to a dialog box.
trainDialog(Train, BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.simple.EncogUtility: Train, using the specified training method, display progress to a dialog box.
TrainFlatNetwork - Interface in org.encog.engine.network.train
TrainFlatNetworkBackPropagation - Class in org.encog.engine.network.train.prop: Train a flat network, using backpropagation.
TrainFlatNetworkBackPropagation(FlatNetwork, EngineDataSet, double, double) - Constructor for class org.encog.engine.network.train.prop.TrainFlatNetworkBackPropagation: Construct a backprop trainer for flat networks.
TrainFlatNetworkManhattan - Class in org.encog.engine.network.train.prop: Train the flat network using Manhattan update rule.
TrainFlatNetworkManhattan(FlatNetwork, EngineDataSet, double) - Constructor for class org.encog.engine.network.train.prop.TrainFlatNetworkManhattan: Construct a trainer for flat networks to use the Manhattan update rule.
TrainFlatNetworkOpenCL - Class in org.encog.engine.network.train.prop: Train a flat network using OpenCL.
TrainFlatNetworkOpenCL(FlatNetwork, EngineDataSet, OpenCLTrainingProfile) - Constructor for class org.encog.engine.network.train.prop.TrainFlatNetworkOpenCL: Train a flat network multithreaded.
TrainFlatNetworkProp - Class in org.encog.engine.network.train.prop: Train a flat network using multithreading, and GPU support.
TrainFlatNetworkProp(FlatNetwork, EngineDataSet) - Constructor for class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Train a flat network multithreaded.
TrainFlatNetworkResilient - Class in org.encog.engine.network.train.prop: Train a flat network using RPROP.
TrainFlatNetworkResilient(FlatNetwork, EngineDataSet, double, double, double) - Constructor for class org.encog.engine.network.train.prop.TrainFlatNetworkResilient: Construct a resilient trainer for flat networks.
TrainFlatNetworkResilient(FlatNetwork, EngineDataSet) - Constructor for class org.encog.engine.network.train.prop.TrainFlatNetworkResilient: Tran a network using RPROP.
TrainFlatNetworkSCG - Class in org.encog.engine.network.train.prop: Train a network using scaled conjugate gradient.
TrainFlatNetworkSCG(FlatNetwork, EngineDataSet) - Constructor for class org.encog.engine.network.train.prop.TrainFlatNetworkSCG: Construct the training object.
TrainingContinuation - Class in org.encog.neural.networks.training.propagation: Allows training to be continued.
TrainingContinuation() - Constructor for class org.encog.neural.networks.training.propagation.TrainingContinuation
TrainingContinuationPersistor - Class in org.encog.persist.persistors: Persist a training continuation persistor.
TrainingContinuationPersistor() - Constructor for class org.encog.persist.persistors.TrainingContinuationPersistor
TrainingDialog - Class in org.encog.util.simple: Display a training dialog.
TrainingDialog() - Constructor for class org.encog.util.simple.TrainingDialog: Construct the training dialog.
TrainingError - Exception in org.encog.neural.networks.training: Thrown when a training error occurs.
TrainingError(String) - Constructor for exception org.encog.neural.networks.training.TrainingError: Construct a message exception.
TrainingError(Throwable) - Constructor for exception org.encog.neural.networks.training.TrainingError: Construct an exception that holds another exception.
TrainingJob - Class in org.encog.neural.networks.training.concurrent.jobs: Base class for all concurrent training jobs.
TrainingJob(BasicNetwork, NeuralDataSet, boolean) - Constructor for class org.encog.neural.networks.training.concurrent.jobs.TrainingJob: Construct a training job.
TrainingSetScore - Class in org.encog.neural.networks.training: Calculate a score based on a training set.
TrainingSetScore(NeuralDataSet) - Constructor for class org.encog.neural.networks.training.TrainingSetScore: Construct a training set score calculation.
trainingSetSize(NeuralDataSet) - Static method in class org.encog.util.simple.TrainingSetUtil
TrainingSetUtil - Class in org.encog.util.simple
TrainingSetUtil() - Constructor for class org.encog.util.simple.TrainingSetUtil
TrainingStatusUtility - Class in org.encog.neural.networks.training: Report the status of Encog training to the cloud.
TrainingStatusUtility(EncogCloud, Train) - Constructor for class org.encog.neural.networks.training.TrainingStatusUtility: Create a training status utility.
trainingToArray(NeuralDataSet) - Static method in class org.encog.util.simple.TrainingSetUtil
TrainInstar - Class in org.encog.neural.networks.training.cpn: Used for Instar training of a CPN neural network.
TrainInstar(BasicNetwork, NeuralDataSet, double) - Constructor for class org.encog.neural.networks.training.cpn.TrainInstar: Construct the instar training object.
TrainOutstar - Class in org.encog.neural.networks.training.cpn: Used for Instar training of a CPN neural network.
TrainOutstar(BasicNetwork, NeuralDataSet, double) - Constructor for class org.encog.neural.networks.training.cpn.TrainOutstar: Construct the outstar trainer.
trainPattern(NeuralData) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Train the specified pattern.
trainToError(BasicNetwork, NeuralDataSet, double) - Static method in class org.encog.util.simple.EncogUtility: Train the network, to a specific error, send the output to the console.
trainToError(Train, BasicNetwork, NeuralDataSet, double) - Static method in class org.encog.util.simple.EncogUtility: Train to a specific error, using the specified training method, send the output to the console.
transpose(Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath: Return the transposition of a matrix.
TruncateSelection - Class in org.encog.solve.genetic.selection: Will be expanded in the future, will define a way parents are selected.
TruncateSelection() - Constructor for class org.encog.solve.genetic.selection.TruncateSelection
TWEAK_DISJOINT - Static variable in class org.encog.neural.networks.training.neat.NEATGenome: The adjustment factor for disjoint genes.
TWEAK_EXCESS - Static variable in class org.encog.neural.networks.training.neat.NEATGenome: The adjustment factor for excess genes.
TWEAK_MATCHED - Static variable in class org.encog.neural.networks.training.neat.NEATGenome: The adjustment factor for matched genes.
twoPassesNeeded() - Method in class org.encog.normalize.DataNormalization
TYPE_BASIC_LAYER - Static variable in class org.encog.persist.EncogPersistedCollection: The type is BasicLayer.
TYPE_BASIC_NET - Static variable in class org.encog.persist.EncogPersistedCollection: The type is BasicNetwork.
TYPE_BINARY - Static variable in class org.encog.persist.EncogPersistedCollection
TYPE_CONTEXT_LAYER - Static variable in class org.encog.persist.EncogPersistedCollection: The type is ContextLayer.
TYPE_DIRECT_SYNAPSE - Static variable in class org.encog.persist.EncogPersistedCollection: The type is DirectSynapse.
TYPE_JAVASCRIPT - Static variable in class org.encog.script.EncogScript
TYPE_NORMALIZATION - Static variable in class org.encog.persist.EncogPersistedCollection: The type is ParseTemplate.
TYPE_ONE2ONE_SYNAPSE - Static variable in class org.encog.persist.EncogPersistedCollection: The type is OneToOneSynapse.
TYPE_POPULATION - Static variable in class org.encog.persist.EncogPersistedCollection: The basic population.
TYPE_PROPERTY - Static variable in class org.encog.persist.EncogPersistedCollection: The type is PropertyData.
TYPE_RADIAL_BASIS_LAYER - Static variable in class org.encog.persist.EncogPersistedCollection: The type is RadialBasisFunctionLayer.
TYPE_SCRIPT - Static variable in class org.encog.persist.EncogPersistedCollection
TYPE_SVM - Static variable in class org.encog.persist.EncogPersistedCollection
TYPE_TEXT - Static variable in class org.encog.persist.EncogPersistedCollection: The type is TextData.
TYPE_TRAINING - Static variable in class org.encog.persist.EncogPersistedCollection: The type is TrainingData.
TYPE_TRAINING_CONTINUATION - Static variable in class org.encog.persist.EncogPersistedCollection: For training continuation.
TYPE_WEIGHTED_SYNAPSE - Static variable in class org.encog.persist.EncogPersistedCollection: The type is WeightedSynapse.
TYPE_WEIGHTLESS_SYNAPSE - Static variable in class org.encog.persist.EncogPersistedCollection: The type is WeightlessSynapse.

U

unflattenWeights() - Method in class org.encog.neural.networks.structure.NeuralStructure: Unflatten the weights.
UnionNeuralDataSet - Class in org.encog.neural.data.union: A UnionNeuralDataSet is used to create a compound data set that is made up of other data sets.
UnionNeuralDataSet(int, int) - Constructor for class org.encog.neural.data.union.UnionNeuralDataSet: Construct the union data set.
UnionNeuralDataSet.UnionIterator - Class in org.encog.neural.data.union: The iterator used to access the UnionNeuralDataSet.
UnionNeuralDataSet.UnionIterator() - Constructor for class org.encog.neural.data.union.UnionNeuralDataSet.UnionIterator: Construct the union iterator.
update() - Method in class org.encog.neural.networks.training.TrainingStatusUtility: Perform an update.
UPDATE_VALUES - Static variable in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Continuation tag for the last values.
updateError(double, double) - Method in class org.encog.engine.util.ErrorCalculation: Update the error with single values.
updateError(double[], double[]) - Method in class org.encog.engine.util.ErrorCalculation: Called to update for each number that should be checked.
updateFlatNetwork() - Method in class org.encog.neural.networks.structure.NeuralStructure: Update the flat network.
updateProperties(String, String, String) - Method in interface org.encog.persist.EncogCollection: Update the properties of an element in the collection.
updateProperties(String, String, String) - Method in class org.encog.persist.EncogMemoryCollection: Update the properties of an element in the collection.
updateProperties(String, String, String) - Method in class org.encog.persist.EncogPersistedCollection: Update any header properties for an Encog object, for example, a rename.
updateWeight(double[], double[], int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkBackPropagation: Update a weight.
updateWeight(double[], double[], int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkManhattan: Calculate the amount to change the weight by.
updateWeight(double[], double[], int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkProp: Update a weight, the means by which weights are updated vary depending on the training.
updateWeight(double[], double[], int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkResilient: Calculate the amount to change the weight by.
updateWeight(double[], double[], int) - Method in class org.encog.engine.network.train.prop.TrainFlatNetworkSCG: Update the weights.
updateWeights() - Method in class org.encog.neural.networks.training.lma.LevenbergMarquardtTraining: Update the weights.
URLUtility - Class in org.encog.util.http: URLUtility: A set of useful utilities for processing URL's.

V

validate(EngineMachineLearning) - Method in class org.encog.engine.validate.BasicMachineLearningValidate: Determine if the network is valid.
validate(EngineMachineLearning) - Method in interface org.encog.engine.validate.ValidateMachineLearning: Determine if the network is valid.
ValidateForFlat - Class in org.encog.neural.networks.structure: Only certain types of networks can be converted to a flat network.
ValidateForFlat() - Constructor for class org.encog.neural.networks.structure.ValidateForFlat
ValidateForOpenCL - Class in org.encog.engine.network.flat: Validate the network to be sure it can run on OpenCL.
ValidateForOpenCL() - Constructor for class org.encog.engine.network.flat.ValidateForOpenCL
ValidateMachineLearning - Interface in org.encog.engine.validate: Interface for validation.
ValidateMachineLearningError - Exception in org.encog.engine.validate: Error from validation.
ValidateMachineLearningError(String) - Constructor for exception org.encog.engine.validate.ValidateMachineLearningError: Construct a message exception.
ValidateMachineLearningError(String, Throwable) - Constructor for exception org.encog.engine.validate.ValidateMachineLearningError: Construct an exception that holds another exception.
ValidateMachineLearningError(Throwable) - Constructor for exception org.encog.engine.validate.ValidateMachineLearningError: Construct an exception that holds another exception.
validateNetworkForTraining(BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.EncogValidate: Validate a network for training.
validateSession(boolean) - Method in class org.encog.cloud.EncogCloud: Validate the session.
value - Variable in class org.encog.mathutil.libsvm.svm_node
valueOf(String) - Static method in enum org.encog.bot.browse.range.Form.Method: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.engine.util.ErrorCalculationMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.mathutil.rbf.RBFEnum: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.data.market.MarketDataType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.data.temporal.TemporalDataDescription.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.networks.structure.FlatUpdateNeeded: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.networks.svm.KernelType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.networks.svm.SVMType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.networks.synapse.neat.NEATNeuronType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.networks.synapse.SynapseType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.networks.training.neat.NEATInnovationType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.prune.NetworkPattern: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.parse.tags.Tag.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.util.time.TimeUnit: Returns the enum constant of this type with the specified name.
values() - Static method in enum org.encog.bot.browse.range.Form.Method: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.engine.util.ErrorCalculationMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.mathutil.rbf.RBFEnum: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.data.market.MarketDataType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.data.temporal.TemporalDataDescription.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.networks.structure.FlatUpdateNeeded: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.networks.svm.KernelType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.networks.svm.SVMType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.networks.synapse.neat.NEATNeuronType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.networks.synapse.SynapseType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.networks.training.neat.NEATInnovationType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.prune.NetworkPattern: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.parse.tags.Tag.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.util.time.TimeUnit: Returns an array containing the constants of this enum type, in the order they are declared.
vectorLength(Matrix) - Static method in class org.encog.mathutil.matrices.MatrixMath: Calculate the length of a vector.
vectorProduct(double[], double[]) - Static method in class org.encog.engine.util.EngineArray: Calculate the product of two vectors (a scalar value).
VERSION - Static variable in class org.encog.Encog: The current engog version, this should be read from the properties.

W

waitFinish() - Method in class org.encog.engine.opencl.EncogCLQueue: Wait until the queue is finished.
waitForComplete() - Method in class org.encog.engine.concurrency.TaskGroup: Wait for all tasks to complete in this group.
waitForFreePerformer() - Method in class org.encog.neural.networks.training.concurrent.ConcurrentTrainingManager: Wait for a free performer.
WebPage - Class in org.encog.bot.browse: Holds a web page that was loaded by the Browse class.
WebPage() - Constructor for class org.encog.bot.browse.WebPage
weight - Variable in class org.encog.mathutil.libsvm.svm_parameter
weight_label - Variable in class org.encog.mathutil.libsvm.svm_parameter
WeightedSynapse - Class in org.encog.neural.networks.synapse: A fully-connected weight based synapse.
WeightedSynapse() - Constructor for class org.encog.neural.networks.synapse.WeightedSynapse: Simple default constructor.
WeightedSynapse(Layer, Layer) - Constructor for class org.encog.neural.networks.synapse.WeightedSynapse: Construct a weighted synapse between the two layers.
WeightedSynapsePersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the WeightedSynapse class.
WeightedSynapsePersistor() - Constructor for class org.encog.persist.persistors.WeightedSynapsePersistor
WeightlessSynapse - Class in org.encog.neural.networks.synapse: A fully connected synapse that simply sums all input to each neuron, no weights are applied.
WeightlessSynapse() - Constructor for class org.encog.neural.networks.synapse.WeightlessSynapse: Simple default constructor.
WeightlessSynapse(Layer, Layer) - Constructor for class org.encog.neural.networks.synapse.WeightlessSynapse: Construct a weighted synapse between the two layers.
WeightlessSynapsePersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the WeightlessSynapse class.
WeightlessSynapsePersistor() - Constructor for class org.encog.persist.persistors.WeightlessSynapsePersistor
winner(NeuralData) - Method in class org.encog.neural.networks.BasicNetwork: Determine the winner for the specified input.
winner(NeuralData) - Method in interface org.encog.neural.networks.Network: Determine the winner for the specified input.
winner(NeuralData) - Method in class org.encog.neural.networks.training.cpn.FindCPN: Calculate the winning neuron from the data, this is the neuron that has the highest output.
write(double[], double[]) - Method in class org.encog.neural.data.buffer.codec.ArrayDataCODEC: Write one record of data to an external destination.
write(double[], double[]) - Method in class org.encog.neural.data.buffer.codec.CSVDataCODEC: Write one record of data to a CSV file.
write(double[], double[]) - Method in interface org.encog.neural.data.buffer.codec.DataSetCODEC: Write one record of data to an external destination.
write(double[], double[]) - Method in class org.encog.neural.data.buffer.codec.ExcelCODEC: Write one record of data to an external destination.
write(double[], double[]) - Method in class org.encog.neural.data.buffer.codec.NeuralDataSetCODEC: Write one record of data to an external destination.
write(int, int, double) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Write the specified row and column.
write(int, double[]) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Write an array at the specified record.
write(double[]) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Write an array.
write(byte) - Method in class org.encog.neural.data.buffer.EncogEGBFile: Write a byte.
write(double[], int) - Method in interface org.encog.normalize.target.NormalizationStorage: Write an array.
write(double[], int) - Method in class org.encog.normalize.target.NormalizationStorageArray1D: Write an array.
write(double[], int) - Method in class org.encog.normalize.target.NormalizationStorageArray2D: Write an array.
write(double[], int) - Method in class org.encog.normalize.target.NormalizationStorageCSV: Write an array.
write(double[], int) - Method in class org.encog.normalize.target.NormalizationStorageEncogCollection
write(double[], int) - Method in class org.encog.normalize.target.NormalizationStorageNeuralDataSet: Write an array.
writeHeader() - Method in class org.encog.persist.PersistWriter: Write the header for the Encog file.
writeln(String) - Method in class org.encog.util.http.FormUtility: Write a string, with a carriage return and linefeed.
writeObject(EncogPersistedObject) - Method in class org.encog.persist.PersistWriter: Write an object.
WriteTags - Class in org.encog.parse.tags.write: Class used to write out tags, such as XML or HTML.
WriteTags(OutputStream) - Constructor for class org.encog.parse.tags.write.WriteTags: Construct an object to write tags.
WriteXML - Class in org.encog.parse.tags.write: Contains specifics to writing XML.
WriteXML(OutputStream) - Constructor for class org.encog.parse.tags.write.WriteXML: Construct an object to write an XML file.

X

x - Variable in class org.encog.mathutil.libsvm.svm_problem
XML2Object - Class in org.encog.persist.persistors.generic: A generic class used to take an XML segment and produce an object for it.
XML2Object() - Constructor for class org.encog.persist.persistors.generic.XML2Object
XMLNeuralDataSet - Class in org.encog.neural.data.xml: A data source that reads XML files.
XMLNeuralDataSet(String, int, int, String, String, String, String) - Constructor for class org.encog.neural.data.xml.XMLNeuralDataSet: Construct an XML neural data set.
XMLNeuralDataSet.XMLNeuralIterator - Class in org.encog.neural.data.xml: An iterator designed to read from XML files.
XMLNeuralDataSet.XMLNeuralIterator() - Constructor for class org.encog.neural.data.xml.XMLNeuralDataSet.XMLNeuralIterator: Construct an iterator to read the XML data.

Y

y - Variable in class org.encog.mathutil.libsvm.svm_problem
YahooFinanceLoader - Class in org.encog.neural.data.market.loader: This class loads financial data from Yahoo.
YahooFinanceLoader() - Constructor for class org.encog.neural.data.market.loader.YahooFinanceLoader
YahooSearch - Class in org.encog.util: YahooSearch: Perform a search using Yahoo.
YahooSearch() - Constructor for class org.encog.util.YahooSearch
YEARS_CENTURY - Static variable in class org.encog.util.time.TimeSpan: Years in a century.
YEARS_MIL - Static variable in class org.encog.util.time.TimeSpan: Years in a mil.
YEARS_SCORE - Static variable in class org.encog.util.time.TimeSpan: Years in a score.

Z

ZAxisGroup - Class in org.encog.normalize.output.zaxis: Used to group Z-Axis fields together.
ZAxisGroup() - Constructor for class org.encog.normalize.output.zaxis.ZAxisGroup

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