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## Uses of Interface
org.encog.ml.data.MLDataSet

Packages that use MLDataSet
org.encog.ml | This package contains all of the classes for Machine Learning.
org.encog.ml.data | This package contains classes to provide data to the Machine Learning Methods.
org.encog.ml.data.basic |
org.encog.ml.data.buffer | This package implements a folded data set.
org.encog.ml.data.buffer.codec | This package contains classes used to encode/decode from the EGB format.
org.encog.ml.data.folded | This package implements a folded data set.
org.encog.ml.data.market |
org.encog.ml.data.specific | This package contains data classes to get data from specific locations.
org.encog.ml.data.temporal |
org.encog.ml.factory | This package contains the Encog Machine Learning Factory.
org.encog.ml.factory.train | This package is used to create trainers.
org.encog.ml.kmeans | This package holds the classes used to implement kmeans clustering.
org.encog.ml.svm | This package contains all of the classes for support vector machines.
org.encog.ml.svm.training | This package holds the classes used for SVM training.
org.encog.ml.train |
org.encog.neural.cpn | This package contains the classes for CPN networks.
org.encog.neural.cpn.training | This package contains the instar and outstar training for the network.
org.encog.neural.data | This package contains compatibility classes to ease the transition to Encog 3.0.
org.encog.neural.data.basic | This package contains compatibility classes to ease the transition to Encog 3.0.
org.encog.neural.flat | Flat neural networks are Encog's higher performance implementation of multi-layer networks.
org.encog.neural.flat.train | This package contains the flat training methods.
org.encog.neural.flat.train.prop | This package contains the propagation training for flat networks.
org.encog.neural.neat |
org.encog.neural.neat.training |
org.encog.neural.networks | This package contains the neural network machine learning methods.
org.encog.neural.networks.training | This package provides training for neural networks.
org.encog.neural.networks.training.concurrent.jobs | This package provides the performers to perform concurrent training jobs.
org.encog.neural.networks.training.lma | This package provides Levenberg Marquardt training for neural networks.
org.encog.neural.networks.training.pnn | This package provides PNN training.
org.encog.neural.networks.training.propagation | This package provides propagation training for neural networks.
org.encog.neural.networks.training.propagation.back | This package provides back propagation training for neural networks.
org.encog.neural.networks.training.propagation.manhattan | This package provides Manhattan propagation training for neural networks.
org.encog.neural.networks.training.propagation.quick | This package provides back propagation training for neural networks.
org.encog.neural.networks.training.propagation.resilient | This package provides resilient propagation training for neural networks.
org.encog.neural.networks.training.propagation.scg | This package provides SCG propagation training for neural networks.
org.encog.neural.networks.training.simple | This package provides simple ADALINE training.
org.encog.neural.prune | This package contains the classes to prune a neural network.
org.encog.neural.rbf | This package contains classes for RBF networks.
org.encog.neural.rbf.training | This package contains a SVD trainer for RBF.
org.encog.neural.som | This package contains classes for the SOM.
org.encog.neural.som.training.basic | This package implements neighborhood training for the SOM.
org.encog.neural.som.training.clustercopy | This package provides a very simple trianing method for SOM's.
org.encog.platformspecific.j2se |
org.encog.platformspecific.j2se.data |
org.encog.platformspecific.j2se.data.image | This package contains classes used to allow images to be Machine Learning Data.
org.encog.plugin | This package holds classes to implement plugins.
org.encog.plugin.system | This package holds the system plugins.
org.encog.util |
org.encog.util.arrayutil |
org.encog.util.benchmark |
org.encog.util.error |
org.encog.util.simple |
org.encog.util.validate |

Uses of MLDataSet in org.encog.ml

Methods in org.encog.ml that return MLDataSet
`MLDataSet` | `MLCluster.createDataSet()` Create a machine learning dataset from the data.

Methods in org.encog.ml with parameters of type MLDataSet
`double` | `MLError.calculateError(MLDataSet data)` Calculate the error of the ML method, given a dataset.

Uses of MLDataSet in org.encog.ml.data

Methods in org.encog.ml.data that return MLDataSet
`MLDataSet` | `MLDataSet.openAdditional()` Opens an additional instance of this dataset.

Uses of MLDataSet in org.encog.ml.data.basic

Classes in org.encog.ml.data.basic that implement MLDataSet
`class` | `BasicMLDataSet` Stores data in an ArrayList.

Methods in org.encog.ml.data.basic that return MLDataSet
`MLDataSet` | `BasicMLDataSet.openAdditional()` Opens an additional instance of this dataset.

Constructors in org.encog.ml.data.basic with parameters of type MLDataSet
`BasicMLDataSet(MLDataSet set)` Copy whatever dataset type is specified into a memory dataset.

Uses of MLDataSet in org.encog.ml.data.buffer

Classes in org.encog.ml.data.buffer that implement MLDataSet
`class` | `BufferedMLDataSet` This class is not memory based, so very long files can be used, without running out of memory.

Methods in org.encog.ml.data.buffer that return MLDataSet
`MLDataSet` | `MemoryDataLoader.external2Memory()` Convert an external file format, such as CSV, to an Encog memory training set.
`MLDataSet` | `BufferedMLDataSet.loadToMemory()` Load the binary dataset to memory.

Methods in org.encog.ml.data.buffer with parameters of type MLDataSet
`void` | `BufferedMLDataSet.load(MLDataSet training)` Load the specified training set.

Uses of MLDataSet in org.encog.ml.data.buffer.codec

Constructors in org.encog.ml.data.buffer.codec with parameters of type MLDataSet
`NeuralDataSetCODEC(MLDataSet theDataset)` Construct a CODEC.

Uses of MLDataSet in org.encog.ml.data.folded

Classes in org.encog.ml.data.folded that implement MLDataSet
`class` | `FoldedDataSet` A folded data set allows you to "fold" the data into several equal(or nearly equal) datasets.

Methods in org.encog.ml.data.folded that return MLDataSet
`MLDataSet` | `FoldedDataSet.getUnderlying()`
`MLDataSet` | `FoldedDataSet.openAdditional()` Opens an additional instance of this dataset.

Constructors in org.encog.ml.data.folded with parameters of type MLDataSet
`FoldedDataSet(MLDataSet theUnderlying)` Create a folded dataset.

Uses of MLDataSet in org.encog.ml.data.market

Classes in org.encog.ml.data.market that implement MLDataSet
`class` | `MarketMLDataSet` A data set that is designed to hold market data.

Uses of MLDataSet in org.encog.ml.data.specific

Classes in org.encog.ml.data.specific that implement MLDataSet
`class` | `CSVNeuralDataSet` An implementation of the NeuralDataSet interface designed to provide a CSV file to the neural network.

Uses of MLDataSet in org.encog.ml.data.temporal

Classes in org.encog.ml.data.temporal that implement MLDataSet
`class` | `TemporalMLDataSet` This class implements a temporal neural data set.

Uses of MLDataSet in org.encog.ml.factory

Methods in org.encog.ml.factory with parameters of type MLDataSet
`MLTrain` | `MLTrainFactory.create(MLMethod method, MLDataSet training, String type, String args)` Create a trainer.

Uses of MLDataSet in org.encog.ml.factory.train

Methods in org.encog.ml.factory.train with parameters of type MLDataSet
`MLTrain` | `PNNTrainFactory.create(MLMethod method, MLDataSet training, String args)` Create a PNN trainer.
`MLTrain` | `ClusterSOMFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a cluster SOM trainer.
`MLTrain` | `RPROPFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a RPROP trainer.
`MLTrain` | `QuickPropFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a quick propagation trainer.
`MLTrain` | `SVMFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a SVM trainer.
`MLTrain` | `AnnealFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create an annealing trainer.
`MLTrain` | `LMAFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a LMA trainer.
`MLTrain` | `ManhattanFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a Manhattan trainer.
`MLTrain` | `RBFSVDFactory.create(MLMethod method, MLDataSet training, String args)` Create a RBF-SVD trainer.
`MLTrain` | `SVMSearchFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a SVM trainer.
`MLTrain` | `BackPropFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a backpropagation trainer.
`MLTrain` | `GeneticFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create an annealing trainer.
`MLTrain` | `NeighborhoodSOMFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a LMA trainer.
`MLTrain` | `SCGFactory.create(MLMethod method, MLDataSet training, String args)` Create a SCG trainer.

Uses of MLDataSet in org.encog.ml.kmeans

Methods in org.encog.ml.kmeans that return MLDataSet
`MLDataSet` | `KMeansCluster.createDataSet()` Create a dataset from the clustered data.

Constructors in org.encog.ml.kmeans with parameters of type MLDataSet
`KMeansClustering(int k, MLDataSet theSet)` Construct the K-Means object.

Uses of MLDataSet in org.encog.ml.svm

Methods in org.encog.ml.svm with parameters of type MLDataSet
`double` | `SVM.calculateError(MLDataSet data)` Calculate the error for this SVM.

Uses of MLDataSet in org.encog.ml.svm.training

Methods in org.encog.ml.svm.training with parameters of type MLDataSet
`static svm_problem` | `EncodeSVMProblem.encode(MLDataSet training, int outputIndex)` Encode the Encog dataset.

Constructors in org.encog.ml.svm.training with parameters of type MLDataSet
`SVMSearchTrain(SVM method, MLDataSet training)` Construct a trainer for an SVM network.
`SVMTrain(SVM method, MLDataSet dataSet)` Construct a trainer for an SVM network.

Uses of MLDataSet in org.encog.ml.train

Methods in org.encog.ml.train that return MLDataSet
`MLDataSet` | `MLTrain.getTraining()`
`MLDataSet` | `BasicTraining.getTraining()`

Methods in org.encog.ml.train with parameters of type MLDataSet
`void` | `BasicTraining.setTraining(MLDataSet training)` Set the training object that this strategy is working with.

Uses of MLDataSet in org.encog.neural.cpn

Methods in org.encog.neural.cpn with parameters of type MLDataSet
`double` | `CPN.calculateError(MLDataSet data)` Calculate the error for this neural network.

Uses of MLDataSet in org.encog.neural.cpn.training

Constructors in org.encog.neural.cpn.training with parameters of type MLDataSet
`TrainInstar(CPN theNetwork, MLDataSet theTraining, double theLearningRate, boolean theInitWeights)` Construct the instar training object.
`TrainOutstar(CPN theNetwork, MLDataSet theTraining, double theLearningRate)` Construct the outstar trainer.

Uses of MLDataSet in org.encog.neural.data

Subinterfaces of MLDataSet in org.encog.neural.data
`interface` | `NeuralDataSet` This is an alias class for Encog 2.5 compatibility.

Uses of MLDataSet in org.encog.neural.data.basic

Classes in org.encog.neural.data.basic that implement MLDataSet
`class` | `BasicNeuralDataSet` This is an alias class for Encog 2.5 compatibility.

Uses of MLDataSet in org.encog.neural.flat

Methods in org.encog.neural.flat with parameters of type MLDataSet
`double` | `FlatNetwork.calculateError(MLDataSet data)` Calculate the error for this neural network.

Uses of MLDataSet in org.encog.neural.flat.train

Methods in org.encog.neural.flat.train that return MLDataSet
`MLDataSet` | `TrainFlatNetwork.getTraining()`

Uses of MLDataSet in org.encog.neural.flat.train.prop

Methods in org.encog.neural.flat.train.prop that return MLDataSet
`MLDataSet` | `TrainFlatNetworkProp.getTraining()`

Constructors in org.encog.neural.flat.train.prop with parameters of type MLDataSet
`GradientWorker(FlatNetwork theNetwork, TrainFlatNetworkProp theOwner, MLDataSet theTraining, int theLow, int theHigh, double[] flatSpot, ErrorFunction ef)` Construct a gradient worker.
`TrainFlatNetworkBackPropagation(FlatNetwork network, MLDataSet training, double theLearningRate, double theMomentum)` Construct a backprop trainer for flat networks.
`TrainFlatNetworkManhattan(FlatNetwork network, MLDataSet training, double theLearningRate)` Construct a trainer for flat networks to use the Manhattan update rule.
`TrainFlatNetworkProp(FlatNetwork network, MLDataSet training)` Train a flat network multithreaded.
`TrainFlatNetworkQPROP(FlatNetwork network, MLDataSet training, double theLearningRate)` Construct a QPROP trainer for flat networks.
`TrainFlatNetworkResilient(FlatNetwork flat, MLDataSet trainingSet)` Tran a network using RPROP.
`TrainFlatNetworkResilient(FlatNetwork network, MLDataSet training, double zeroTolerance, double initialUpdate, double maxStep)` Construct a resilient trainer for flat networks.
`TrainFlatNetworkSCG(FlatNetwork network, MLDataSet training)` Construct the training object.

Uses of MLDataSet in org.encog.neural.neat

Methods in org.encog.neural.neat with parameters of type MLDataSet
`double` | `NEATNetwork.calculateError(MLDataSet data)` Calculate the error for this neural network.

Uses of MLDataSet in org.encog.neural.neat.training

Methods in org.encog.neural.neat.training that return MLDataSet
`MLDataSet` | `NEATTraining.getTraining()` Returns null, does not use a training set, rather uses a score function.

Uses of MLDataSet in org.encog.neural.networks

Methods in org.encog.neural.networks with parameters of type MLDataSet
`double` | `BasicNetwork.calculateError(MLDataSet data)` Calculate the error for this neural network.

Uses of MLDataSet in org.encog.neural.networks.training

Constructors in org.encog.neural.networks.training with parameters of type MLDataSet
`TrainingSetScore(MLDataSet training)` Construct a training set score calculation.

Uses of MLDataSet in org.encog.neural.networks.training.concurrent.jobs

Methods in org.encog.neural.networks.training.concurrent.jobs that return MLDataSet
`MLDataSet` | `TrainingJob.getTraining()`

Methods in org.encog.neural.networks.training.concurrent.jobs with parameters of type MLDataSet
`void` | `TrainingJob.setTraining(MLDataSet training)`

Constructors in org.encog.neural.networks.training.concurrent.jobs with parameters of type MLDataSet
`BPROPJob(BasicNetwork network, MLDataSet training, boolean loadToMemory, double learningRate, double momentum)` Construct a job definition for RPROP.
`RPROPJob(BasicNetwork network, MLDataSet training, boolean loadToMemory)` Construct an RPROP job.
`TrainingJob(BasicNetwork network, MLDataSet training, boolean loadToMemory)` Construct a training job.

Uses of MLDataSet in org.encog.neural.networks.training.lma

Constructors in org.encog.neural.networks.training.lma with parameters of type MLDataSet
`LevenbergMarquardtTraining(BasicNetwork network, MLDataSet training)` Construct the LMA object.

Uses of MLDataSet in org.encog.neural.networks.training.pnn

Methods in org.encog.neural.networks.training.pnn with parameters of type MLDataSet
`double` | `TrainBasicPNN.calculateError(MLDataSet training, boolean deriv)` Calculate the error for the entire training set.

Constructors in org.encog.neural.networks.training.pnn with parameters of type MLDataSet
`TrainBasicPNN(BasicPNN network, MLDataSet training)` Train a BasicPNN.

Uses of MLDataSet in org.encog.neural.networks.training.propagation

Constructors in org.encog.neural.networks.training.propagation with parameters of type MLDataSet
`Propagation(ContainsFlat network, MLDataSet training)` Construct a propagation object.

Uses of MLDataSet in org.encog.neural.networks.training.propagation.back

Constructors in org.encog.neural.networks.training.propagation.back with parameters of type MLDataSet
`Backpropagation(ContainsFlat network, MLDataSet training)` Create a class to train using backpropagation.
`Backpropagation(ContainsFlat network, MLDataSet training, double learnRate, double momentum)`

Uses of MLDataSet in org.encog.neural.networks.training.propagation.manhattan

Constructors in org.encog.neural.networks.training.propagation.manhattan with parameters of type MLDataSet
`ManhattanPropagation(ContainsFlat network, MLDataSet training, double learnRate)` Construct a Manhattan propagation training object.

Uses of MLDataSet in org.encog.neural.networks.training.propagation.quick

Constructors in org.encog.neural.networks.training.propagation.quick with parameters of type MLDataSet
`QuickPropagation(ContainsFlat network, MLDataSet training)` Construct a QPROP trainer for flat networks.
`QuickPropagation(ContainsFlat network, MLDataSet training, double learnRate)` Construct a QPROP trainer for flat networks.

Uses of MLDataSet in org.encog.neural.networks.training.propagation.resilient

Constructors in org.encog.neural.networks.training.propagation.resilient with parameters of type MLDataSet
`ResilientPropagation(ContainsFlat network, MLDataSet training)` Construct an RPROP trainer, allows an OpenCL device to be specified.
`ResilientPropagation(ContainsFlat network, MLDataSet training, double initialUpdate, double maxStep)` Construct a resilient training object, allow the training parameters to be specified.

Uses of MLDataSet in org.encog.neural.networks.training.propagation.scg

Constructors in org.encog.neural.networks.training.propagation.scg with parameters of type MLDataSet
`ScaledConjugateGradient(ContainsFlat network, MLDataSet training)` Construct a training class.

Uses of MLDataSet in org.encog.neural.networks.training.simple

Constructors in org.encog.neural.networks.training.simple with parameters of type MLDataSet
`TrainAdaline(BasicNetwork network, MLDataSet training, double learningRate)` Construct an ADALINE trainer.

Uses of MLDataSet in org.encog.neural.prune

Methods in org.encog.neural.prune that return MLDataSet
`MLDataSet` | `PruneIncremental.getTraining()`

Constructors in org.encog.neural.prune with parameters of type MLDataSet
`PruneIncremental(MLDataSet training, NeuralNetworkPattern pattern, int iterations, int weightTries, int numTopResults, StatusReportable report)` Construct an object to determine the optimal number of hidden layers and neurons for the specified training data and pattern.

Uses of MLDataSet in org.encog.neural.rbf

Methods in org.encog.neural.rbf with parameters of type MLDataSet
`double` | `RBFNetwork.calculateError(MLDataSet data)` Calculate the error for this neural network.

Uses of MLDataSet in org.encog.neural.rbf.training

Constructors in org.encog.neural.rbf.training with parameters of type MLDataSet
`SVDTraining(RBFNetwork network, MLDataSet training)` Construct the training object.

Uses of MLDataSet in org.encog.neural.som

Methods in org.encog.neural.som with parameters of type MLDataSet
`double` | `SOM.calculateError(MLDataSet data)` Calculate the error of the ML method, given a dataset.

Uses of MLDataSet in org.encog.neural.som.training.basic

Constructors in org.encog.neural.som.training.basic with parameters of type MLDataSet
`BasicTrainSOM(SOM network, double learningRate, MLDataSet training, NeighborhoodFunction neighborhood)` Create an instance of competitive training.

Uses of MLDataSet in org.encog.neural.som.training.clustercopy

Constructors in org.encog.neural.som.training.clustercopy with parameters of type MLDataSet
`SOMClusterCopyTraining(SOM network, MLDataSet training)` Construct the object.

Uses of MLDataSet in org.encog.platformspecific.j2se

Methods in org.encog.platformspecific.j2se with parameters of type MLDataSet
`static void` | `TrainingDialog.trainDialog(BasicNetwork network, MLDataSet trainingSet)` Train using SCG and display progress to a dialog box.
`static void` | `TrainingDialog.trainDialog(MLTrain train, BasicNetwork network, MLDataSet trainingSet)` Train, using the specified training method, display progress to a dialog box.

Uses of MLDataSet in org.encog.platformspecific.j2se.data

Classes in org.encog.platformspecific.j2se.data that implement MLDataSet
`class` | `SQLNeuralDataSet` A dataset based on a SQL query.

Uses of MLDataSet in org.encog.platformspecific.j2se.data.image

Classes in org.encog.platformspecific.j2se.data.image that implement MLDataSet
`class` | `ImageMLDataSet` Store a collection of images for training with a neural network.

Uses of MLDataSet in org.encog.plugin

Methods in org.encog.plugin with parameters of type MLDataSet
`MLTrain` | `EncogPluginService1.createTraining(MLMethod method, MLDataSet training, String type, String args)` Create a trainer.

Uses of MLDataSet in org.encog.plugin.system

Methods in org.encog.plugin.system with parameters of type MLDataSet
`MLTrain` | `SystemTrainingPlugin.createTraining(MLMethod method, MLDataSet training, String type, String args)`
`MLTrain` | `SystemMethodsPlugin.createTraining(MLMethod method, MLDataSet training, String type, String args)` Create a trainer.
`MLTrain` | `SystemActivationPlugin.createTraining(MLMethod method, MLDataSet training, String type, String args)` Create a trainer.

Uses of MLDataSet in org.encog.util

Methods in org.encog.util with parameters of type MLDataSet
`static void` | `EncogValidate.validateNetworkForTraining(ContainsFlat network, MLDataSet training)` Validate a network for training.

Uses of MLDataSet in org.encog.util.arrayutil

Methods in org.encog.util.arrayutil that return MLDataSet
`MLDataSet` | `TemporalWindowArray.process(double[] data)` Process the array.

Uses of MLDataSet in org.encog.util.benchmark

Methods in org.encog.util.benchmark with parameters of type MLDataSet
`static int` | `Evaluate.evaluateTrain(BasicNetwork network, MLDataSet training)` Evaluate how long it takes to calculate the error for the network.
`static void` | `RandomTrainingFactory.generate(MLDataSet training, long seed, int count, double min, double max)` Generate random training into a training set.

Uses of MLDataSet in org.encog.util.error

Methods in org.encog.util.error with parameters of type MLDataSet
`static double` | `CalculateRegressionError.calculateError(MLRegression method, MLDataSet data)`

Uses of MLDataSet in org.encog.util.simple

Methods in org.encog.util.simple that return MLDataSet
`static MLDataSet` | `EncogUtility.loadCSV2Memory(String filename, int input, int ideal, boolean headers, CSVFormat format, boolean significance)` Load CSV to memory.
`static MLDataSet` | `TrainingSetUtil.loadCSVTOMemory(CSVFormat format, String filename, boolean headers, int inputSize, int idealSize)` Load a CSV file into a memory dataset.
`static MLDataSet` | `EncogUtility.loadEGB2Memory(File filename)`

Methods in org.encog.util.simple with parameters of type MLDataSet
`static double` | `EncogUtility.calculateClassificationError(MLClassification method, MLDataSet data)`
`static double` | `EncogUtility.calculateRegressionError(MLRegression method, MLDataSet data)`
`static void` | `EncogUtility.evaluate(MLRegression network, MLDataSet training)` Evaluate the network and display (to the console) the output for every value in the training set.
`static void` | `EncogUtility.saveCSV(File targetFile, CSVFormat format, MLDataSet set)`
`static void` | `EncogUtility.saveEGB(File f, MLDataSet data)` Save a training set to an EGB file.
`static void` | `EncogUtility.trainConsole(BasicNetwork network, MLDataSet trainingSet, int minutes)` Train the neural network, using SCG training, and output status to the console.
`static void` | `EncogUtility.trainConsole(MLTrain train, BasicNetwork network, MLDataSet trainingSet, int minutes)` Train the network, using the specified training algorithm, and send the output to the console.
`static ObjectPair<double[][],double[][]>` | `TrainingSetUtil.trainingToArray(MLDataSet training)`
`static void` | `EncogUtility.trainToError(MLMethod method, MLDataSet dataSet, double error)` Train the method, to a specific error, send the output to the console.

Uses of MLDataSet in org.encog.util.validate

Methods in org.encog.util.validate with parameters of type MLDataSet
`static void` | `ValidateNetwork.validateMethodToData(MLMethod method, MLDataSet training)`

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