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

Packages that use MLDataSet
org.encog.mathutil.matrices.hessian |
org.encog.ml |
org.encog.ml.bayesian |
org.encog.ml.bayesian.training |
org.encog.ml.bayesian.training.estimator |
org.encog.ml.bayesian.training.search |
org.encog.ml.bayesian.training.search.k2 |
org.encog.ml.data |
org.encog.ml.data.basic |
org.encog.ml.data.buffer |
org.encog.ml.data.buffer.codec |
org.encog.ml.data.folded |
org.encog.ml.data.market |
org.encog.ml.data.specific |
org.encog.ml.data.temporal |
org.encog.ml.factory |
org.encog.ml.factory.train |
org.encog.ml.fitting.gaussian |
org.encog.ml.fitting.linear |
org.encog.ml.hmm |
org.encog.ml.hmm.alog |
org.encog.ml.hmm.distributions |
org.encog.ml.hmm.train.bw |
org.encog.ml.hmm.train.kmeans |
org.encog.ml.kmeans |
org.encog.ml.svm |
org.encog.ml.svm.training |
org.encog.ml.train |
org.encog.ml.train.strategy.end |
org.encog.neural.cpn |
org.encog.neural.cpn.training |
org.encog.neural.data |
org.encog.neural.data.basic |
org.encog.neural.flat |
org.encog.neural.neat |
org.encog.neural.neat.training |
org.encog.neural.networks |
org.encog.neural.networks.training |
org.encog.neural.networks.training.concurrent.jobs |
org.encog.neural.networks.training.lma |
org.encog.neural.networks.training.nm |
org.encog.neural.networks.training.pnn |
org.encog.neural.networks.training.propagation |
org.encog.neural.networks.training.propagation.back |
org.encog.neural.networks.training.propagation.manhattan |
org.encog.neural.networks.training.propagation.quick |
org.encog.neural.networks.training.propagation.resilient |
org.encog.neural.networks.training.propagation.scg |
org.encog.neural.networks.training.pso |
org.encog.neural.networks.training.simple |
org.encog.neural.pnn |
org.encog.neural.prune |
org.encog.neural.rbf |
org.encog.neural.rbf.training |
org.encog.neural.som |
org.encog.neural.som.training.basic |
org.encog.neural.som.training.clustercopy |
org.encog.platformspecific.j2se |
org.encog.platformspecific.j2se.data |
org.encog.platformspecific.j2se.data.image |
org.encog.plugin |
org.encog.plugin.system |
org.encog.util |
org.encog.util.arrayutil |
org.encog.util.benchmark |
org.encog.util.error |
org.encog.util.normalize.target |
org.encog.util.simple |
org.encog.util.validate |

Uses of MLDataSet in org.encog.mathutil.matrices.hessian

Fields in org.encog.mathutil.matrices.hessian declared as MLDataSet
`protected MLDataSet` | `BasicHessian.training` The training data that provides the ideal values.

Methods in org.encog.mathutil.matrices.hessian with parameters of type MLDataSet
`void` | `ComputeHessian.init(BasicNetwork theNetwork, MLDataSet theTraining)` Init the class.
`void` | `HessianFD.init(BasicNetwork theNetwork, MLDataSet theTraining)` Init the class.
`void` | `HessianCR.init(BasicNetwork theNetwork, MLDataSet theTraining)` Init the class.
`void` | `BasicHessian.init(BasicNetwork theNetwork, MLDataSet theTraining)` Init the class.

Constructors in org.encog.mathutil.matrices.hessian with parameters of type MLDataSet
`ChainRuleWorker(FlatNetwork theNetwork, MLDataSet theTraining, int theLow, int theHigh)` Construct the chain rule worker.

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.
`int[]` | `MLStateSequence.getStatesForSequence(MLDataSet oseq)` Get the sates for the given sequence.
`double` | `MLStateSequence.probability(MLDataSet oseq)` Determine the probability of the specified sequence.
`double` | `MLStateSequence.probability(MLDataSet seq, int[] states)` Determine the probability for the specified sequence and states.

Uses of MLDataSet in org.encog.ml.bayesian

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

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

Constructors in org.encog.ml.bayesian.training with parameters of type MLDataSet
`TrainBayesian(BayesianNetwork theNetwork, MLDataSet theData, int theMaximumParents)` Construct a Bayesian trainer.
`TrainBayesian(BayesianNetwork theNetwork, MLDataSet theData, int theMaximumParents, BayesianInit theInit, BayesSearch theSearch, BayesEstimator theEstimator)` Construct a Bayesian trainer.

Uses of MLDataSet in org.encog.ml.bayesian.training.estimator

Methods in org.encog.ml.bayesian.training.estimator with parameters of type MLDataSet
`void` | `EstimatorNone.init(TrainBayesian theTrainer, BayesianNetwork theNetwork, MLDataSet theData)` Init the estimator.
`void` | `SimpleEstimator.init(TrainBayesian theTrainer, BayesianNetwork theNetwork, MLDataSet theData)` Init the estimator.
`void` | `BayesEstimator.init(TrainBayesian theTrainer, BayesianNetwork theNetwork, MLDataSet theData)` Init the estimator.

Uses of MLDataSet in org.encog.ml.bayesian.training.search

Methods in org.encog.ml.bayesian.training.search with parameters of type MLDataSet
`void` | `SearchNone.init(TrainBayesian theTrainer, BayesianNetwork theNetwork, MLDataSet theData)` Init the search object.

Uses of MLDataSet in org.encog.ml.bayesian.training.search.k2

Methods in org.encog.ml.bayesian.training.search.k2 with parameters of type MLDataSet
`void` | `BayesSearch.init(TrainBayesian theTrainer, BayesianNetwork theNetwork, MLDataSet theData)` Init the search object.
`void` | `SearchK2.init(TrainBayesian theTrainer, BayesianNetwork theNetwork, MLDataSet theData)` Init the search object.

Uses of MLDataSet in org.encog.ml.data

Subinterfaces of MLDataSet in org.encog.ml.data
`interface` | `MLSequenceSet` A sequence set is a collection of data sets.

Methods in org.encog.ml.data that return MLDataSet
`MLDataSet` | `MLSequenceSet.getSequence(int i)` Get an individual sequence.
`MLDataSet` | `MLDataSet.openAdditional()` Opens an additional instance of this dataset.

Methods in org.encog.ml.data that return types with arguments of type MLDataSet
`Collection<MLDataSet>` | `MLSequenceSet.getSequences()`

Methods in org.encog.ml.data with parameters of type MLDataSet
`void` | `MLSequenceSet.add(MLDataSet sequence)` Add a new sequence.

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.
`class` | `BasicMLSequenceSet` A basic implementation of the MLSequenceSet.

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

Methods in org.encog.ml.data.basic that return types with arguments of type MLDataSet
`Collection<MLDataSet>` | `BasicMLSequenceSet.getSequences()`

Methods in org.encog.ml.data.basic with parameters of type MLDataSet
`void` | `BasicMLSequenceSet.add(MLDataSet sequence)`
`static List<MLDataPair>` | `BasicMLDataSet.toList(MLDataSet theSet)` Concert the data set to a list.

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.
`BasicMLSequenceSet(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` | `ManhattanFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a Manhattan trainer.
`MLTrain` | `RPROPFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a RPROP trainer.
`MLTrain` | `NeighborhoodSOMFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a LMA trainer.
`MLTrain` | `PNNTrainFactory.create(MLMethod method, MLDataSet training, String args)` Create a PNN trainer.
`MLTrain` | `SCGFactory.create(MLMethod method, MLDataSet training, String args)` Create a SCG trainer.
`MLTrain` | `NelderMeadFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a Nelder Mead trainer.
`MLTrain` | `QuickPropFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a quick propagation trainer.
`MLTrain` | `SVMSearchFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a SVM trainer.
`MLTrain` | `ClusterSOMFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a cluster SOM trainer.
`MLTrain` | `GeneticFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create an annealing trainer.
`MLTrain` | `TrainBayesianFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a K2 trainer.
`MLTrain` | `RBFSVDFactory.create(MLMethod method, MLDataSet training, String args)` Create a RBF-SVD trainer.
`MLTrain` | `BackPropFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a backpropagation trainer.
`MLTrain` | `LMAFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a LMA trainer.
`MLTrain` | `SVMFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a SVM trainer.
`MLTrain` | `PSOFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create a PSO trainer.
`MLTrain` | `AnnealFactory.create(MLMethod method, MLDataSet training, String argsStr)` Create an annealing trainer.

Uses of MLDataSet in org.encog.ml.fitting.gaussian

Methods in org.encog.ml.fitting.gaussian that return MLDataSet
`MLDataSet` | `TrainGaussian.getTraining()`

Constructors in org.encog.ml.fitting.gaussian with parameters of type MLDataSet
`TrainGaussian(GaussianFitting theMethod, MLDataSet theTraining)`

Uses of MLDataSet in org.encog.ml.fitting.linear

Methods in org.encog.ml.fitting.linear that return MLDataSet
`MLDataSet` | `TrainLinearRegression.getTraining()`

Methods in org.encog.ml.fitting.linear with parameters of type MLDataSet
`double` | `LinearRegression.calculateError(MLDataSet data)`

Constructors in org.encog.ml.fitting.linear with parameters of type MLDataSet
`TrainLinearRegression(LinearRegression theMethod, MLDataSet theTraining)`

Uses of MLDataSet in org.encog.ml.hmm

Methods in org.encog.ml.hmm with parameters of type MLDataSet
`int[]` | `HiddenMarkovModel.getStatesForSequence(MLDataSet seq)`
`double` | `HiddenMarkovModel.lnProbability(MLDataSet seq)`
`double` | `HiddenMarkovModel.probability(MLDataSet seq)`
`double` | `HiddenMarkovModel.probability(MLDataSet seq, int[] states)`

Uses of MLDataSet in org.encog.ml.hmm.alog

Methods in org.encog.ml.hmm.alog that return MLDataSet
`MLDataSet` | `MarkovGenerator.observationSequence(int length)`

Methods in org.encog.ml.hmm.alog with parameters of type MLDataSet
`protected void` | `ForwardBackwardScaledCalculator.computeAlpha(HiddenMarkovModel hmm, MLDataSet oseq)`
`protected void` | `ForwardBackwardCalculator.computeAlpha(HiddenMarkovModel hmm, MLDataSet oseq)` Compute alpha.
`protected void` | `ForwardBackwardScaledCalculator.computeBeta(HiddenMarkovModel hmm, MLDataSet oseq)`
`protected void` | `ForwardBackwardCalculator.computeBeta(HiddenMarkovModel hmm, MLDataSet oseq)` Compute the beta step.

Constructors in org.encog.ml.hmm.alog with parameters of type MLDataSet
`ForwardBackwardCalculator(MLDataSet oseq, HiddenMarkovModel hmm)` Construct the forward/backward calculator.
`ForwardBackwardCalculator(MLDataSet oseq, HiddenMarkovModel hmm, EnumSet<ForwardBackwardCalculator.Computation> flags)` Construct the object.
`ForwardBackwardScaledCalculator(MLDataSet oseq, HiddenMarkovModel hmm)`
`ForwardBackwardScaledCalculator(MLDataSet oseq, HiddenMarkovModel hmm, EnumSet<ForwardBackwardCalculator.Computation> flags)`
`ViterbiCalculator(MLDataSet oseq, HiddenMarkovModel hmm)`

Uses of MLDataSet in org.encog.ml.hmm.distributions

Methods in org.encog.ml.hmm.distributions with parameters of type MLDataSet
`void` | `ContinousDistribution.fit(MLDataSet co)` Fit this distribution to the specified data set.
`void` | `StateDistribution.fit(MLDataSet set)` Fit this distribution to the specified data set.
`void` | `DiscreteDistribution.fit(MLDataSet co)` Fit this distribution to the specified data.
`void` | `ContinousDistribution.fit(MLDataSet co, double[] weights)` Fit this distribution to the specified data set, given the specified weights, per element.
`void` | `StateDistribution.fit(MLDataSet set, double[] weights)` Fit this distribution to the specified data set, given the specified weights, per element.
`void` | `DiscreteDistribution.fit(MLDataSet co, double[] weights)` Fit this distribution to the specified data, with weights.

Uses of MLDataSet in org.encog.ml.hmm.train.bw

Methods in org.encog.ml.hmm.train.bw that return MLDataSet
`MLDataSet` | `BaseBaumWelch.getTraining()`

Methods in org.encog.ml.hmm.train.bw with parameters of type MLDataSet
`abstract double[][][]` | `BaseBaumWelch.estimateXi(MLDataSet sequence, ForwardBackwardCalculator fbc, HiddenMarkovModel hmm)`
`double[][][]` | `TrainBaumWelch.estimateXi(MLDataSet sequence, ForwardBackwardCalculator fbc, HiddenMarkovModel hmm)`
`double[][][]` | `TrainBaumWelchScaled.estimateXi(MLDataSet sequence, ForwardBackwardCalculator fbc, HiddenMarkovModel hmm)`
`abstract ForwardBackwardCalculator` | `BaseBaumWelch.generateForwardBackwardCalculator(MLDataSet sequence, HiddenMarkovModel hmm)`
`ForwardBackwardCalculator` | `TrainBaumWelch.generateForwardBackwardCalculator(MLDataSet sequence, HiddenMarkovModel hmm)`
`ForwardBackwardCalculator` | `TrainBaumWelchScaled.generateForwardBackwardCalculator(MLDataSet sequence, HiddenMarkovModel hmm)`

Uses of MLDataSet in org.encog.ml.hmm.train.kmeans

Methods in org.encog.ml.hmm.train.kmeans that return MLDataSet
`MLDataSet` | `TrainKMeans.getTraining()`

Constructors in org.encog.ml.hmm.train.kmeans with parameters of type MLDataSet
`Clusters(int k, MLDataSet observations)`

Uses of MLDataSet in org.encog.ml.kmeans

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

Constructors in org.encog.ml.kmeans with parameters of type MLDataSet
`KMeansClustering(int theK, 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` | `BasicTraining.getTraining()`
`MLDataSet` | `MLTrain.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.ml.train.strategy.end

Constructors in org.encog.ml.train.strategy.end with parameters of type MLDataSet
`EarlyStoppingStrategy(MLDataSet theValidationSet, MLDataSet theTestSet)` Construct the early stopping strategy.
`EarlyStoppingStrategy(MLDataSet theValidationSet, MLDataSet theTestSet, int theStripLength, double theAlpha, double theMinEfficiency)` Construct the early stopping strategy.

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.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.
`LevenbergMarquardtTraining(BasicNetwork network, MLDataSet training, ComputeHessian h)` Construct the LMA object.

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

Constructors in org.encog.neural.networks.training.nm with parameters of type MLDataSet
`NelderMeadTraining(BasicNetwork network, MLDataSet training)` Construct a Nelder Mead trainer with a step size of 100.
`NelderMeadTraining(BasicNetwork network, MLDataSet training, double stepValue)` Construct a Nelder Mead trainer with a definable step.

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
`GradientWorker(FlatNetwork theNetwork, Propagation theOwner, MLDataSet theTraining, int theLow, int theHigh, double[] flatSpot, ErrorFunction ef)` Construct a gradient worker.
`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 theLearnRate, double theMomentum)`

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 theLearnRate)` 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.pso

Constructors in org.encog.neural.networks.training.pso with parameters of type MLDataSet
`NeuralPSO(BasicNetwork network, MLDataSet trainingSet)` Construct a PSO using a training set score function, 20 particles and the NguyenWidrowRandomizer randomizer.

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.pnn

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

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` | `SystemActivationPlugin.createTraining(MLMethod method, MLDataSet training, String type, String args)` Create a trainer.
`MLTrain` | `SystemMethodsPlugin.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.
`MLDataSet` | `TemporalWindowArray.process(double[][] data)` Processes the specified data array in an IMLDataset.

Uses of MLDataSet in org.encog.util.benchmark

Methods in org.encog.util.benchmark that return MLDataSet
`static MLDataSet` | `EncoderTrainingFactory.generateTraining(int inputCount, boolean compl)` Generate an encoder training set over the range [0.0,1.0].
`static MLDataSet` | `EncoderTrainingFactory.generateTraining(int inputCount, boolean compl, double min, double max)` Generate an encoder over the specified range.
`static MLDataSet` | `EncoderTrainingFactory.generateTraining(int inputCount, boolean compl, double inputMin, double inputMax, double outputMin, double outputMax)`

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.normalize.target

Methods in org.encog.util.normalize.target that return MLDataSet
`MLDataSet` | `NormalizationStorageNeuralDataSet.getDataset()`

Constructors in org.encog.util.normalize.target with parameters of type MLDataSet
`NormalizationStorageNeuralDataSet(MLDataSet dataset)` Construct a normalized neural storage class to hold 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)` Calculate the classification error.
`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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