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

- Packages that use MLDataSet
  Package | Description
  --- | ---
  org.encog.app.analyst.commands |
  org.encog.app.analyst.util |
  org.encog.ensemble |
  org.encog.ensemble.data |
  org.encog.ensemble.data.factories |
  org.encog.ensemble.training |
  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.auto |
  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.data.versatile |
  org.encog.ml.ea.train.basic |
  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.model |
  org.encog.ml.prg |
  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.freeform |
  org.encog.neural.freeform.training |
  org.encog.neural.neat |
  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.data |
  org.encog.util.error |
  org.encog.util.normalize.target |
  org.encog.util.simple |
  org.encog.util.validate |

- - ### Uses of MLDataSet in org.encog.app.analyst.commands

    Methods in org.encog.app.analyst.commands that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | Cmd.`obtainTrainingSet()` Obtain the training set.

  - ### Uses of MLDataSet in org.encog.app.analyst.util

    Methods in org.encog.app.analyst.util that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | AnalystUtility.`loadCSV(File file)` Load a CSV file into an MLDataSet.
    `MLDataSet` | AnalystUtility.`loadCSV(String filename)` Load a CSV file into an MLDataSet.

  - ### Uses of MLDataSet in org.encog.ensemble

    Fields in org.encog.ensemble declared as MLDataSet
    Modifier and Type | Field and Description
    --- | ---
    `protected MLDataSet` | Ensemble.`aggregatorDataSet`

    Methods in org.encog.ensemble that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | Ensemble.`getTrainingSet(int setNumber)` Extract a specific training set from the Ensemble

    Methods in org.encog.ensemble with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLTrain` | EnsembleTrainFactory.`getTraining(MLMethod method, MLDataSet trainingData)`
    `void` | Ensemble.`setTrainingData(MLDataSet data)` Set which training data to base the training on

  - ### Uses of MLDataSet in org.encog.ensemble.data

    Classes in org.encog.ensemble.data that implement MLDataSet
    Modifier and Type | Class and Description
    --- | ---
    `class` | `EnsembleDataSet`

    Methods in org.encog.ensemble.data that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | EnsembleDataSet.`openAdditional()`

    Constructors in org.encog.ensemble.data with parameters of type MLDataSet
    Constructor and Description
    `EnsembleDataSet(MLDataSet mlds)`

  - ### Uses of MLDataSet in org.encog.ensemble.data.factories

    Fields in org.encog.ensemble.data.factories declared as MLDataSet
    Modifier and Type | Field and Description
    --- | ---
    `protected MLDataSet` | EnsembleDataSetFactory.`dataSource`

    Methods in org.encog.ensemble.data.factories that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | EnsembleDataSetFactory.`getInputData()`

    Methods in org.encog.ensemble.data.factories with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `void` | EnsembleDataSetFactory.`setInputData(MLDataSet dataSource)`

  - ### Uses of MLDataSet in org.encog.ensemble.training

    Methods in org.encog.ensemble.training with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLTrain` | ManhattanPropagationFactory.`getTraining(MLMethod mlMethod, MLDataSet trainingData)`
    `MLTrain` | ResilientPropagationFactory.`getTraining(MLMethod mlMethod, MLDataSet trainingData)`
    `MLTrain` | ScaledConjugateGradientFactory.`getTraining(MLMethod mlMethod, MLDataSet trainingData)`
    `MLTrain` | LevenbergMarquardtFactory.`getTraining(MLMethod mlMethod, MLDataSet trainingData)`
    `MLTrain` | BackpropagationFactory.`getTraining(MLMethod mlMethod, MLDataSet trainingData)`

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

    Fields in org.encog.mathutil.matrices.hessian declared as MLDataSet
    Modifier and Type | Field and Description
    --- | ---
    `protected MLDataSet` | BasicHessian.`training` The training data that provides the ideal values.

    Methods in org.encog.mathutil.matrices.hessian with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `void` | HessianFD.`init(BasicNetwork theNetwork, MLDataSet theTraining)` Init the class.
    `void` | HessianCR.`init(BasicNetwork theNetwork, MLDataSet theTraining)` Init the class.
    `void` | ComputeHessian.`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
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | MLCluster.`createDataSet()` Create a machine learning dataset from the data.

    Methods in org.encog.ml with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `void` | SimpleEstimator.`init(TrainBayesian theTrainer, BayesianNetwork theNetwork, MLDataSet theData)` Init the estimator.
    `void` | EstimatorNone.`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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `void` | SearchK2.`init(TrainBayesian theTrainer, BayesianNetwork theNetwork, MLDataSet theData)` Init the search object.
    `void` | BayesSearch.`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
    Modifier and Type | Interface and Description
    --- | ---
    `interface` | `MLSequenceSet` A sequence set is a collection of data sets.

    Methods in org.encog.ml.data that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `Collection<MLDataSet>` | MLSequenceSet.`getSequences()`

    Methods in org.encog.ml.data with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `void` | MLSequenceSet.`add(MLDataSet sequence)` Add a new sequence.

  - ### Uses of MLDataSet in org.encog.ml.data.auto

    Classes in org.encog.ml.data.auto that implement MLDataSet
    Modifier and Type | Class and Description
    --- | ---
    `class` | `AutoFloatDataSet`

    Methods in org.encog.ml.data.auto that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | AutoFloatDataSet.`openAdditional()`

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

    Classes in org.encog.ml.data.basic that implement MLDataSet
    Modifier and Type | Class and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | BasicMLSequenceSet.`getSequence(int i)`
    `MLDataSet` | BasicMLSequenceSet.`openAdditional()` Opens an additional instance of this dataset.
    `MLDataSet` | BasicMLDataSet.`openAdditional()` Opens an additional instance of this dataset.

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

    Methods in org.encog.ml.data.basic with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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
    Modifier and Type | Class and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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
    Modifier and Type | Class and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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
    Modifier and Type | Class and Description
    --- | ---
    `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
    Modifier and Type | Class and Description
    --- | ---
    `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
    Modifier and Type | Class and Description
    --- | ---
    `class` | `TemporalMLDataSet` This class implements a temporal neural data set.

  - ### Uses of MLDataSet in org.encog.ml.data.versatile

    Classes in org.encog.ml.data.versatile that implement MLDataSet
    Modifier and Type | Class and Description
    --- | ---
    `class` | `MatrixMLDataSet` The MatrixMLDataSet can use a large 2D matrix of doubles to internally hold data.
    `class` | `VersatileMLDataSet` The versatile dataset supports several advanced features.

    Methods in org.encog.ml.data.versatile that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | MatrixMLDataSet.`openAdditional()` Opens an additional instance of this dataset.

  - ### Uses of MLDataSet in org.encog.ml.ea.train.basic

    Methods in org.encog.ml.ea.train.basic that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | TrainEA.`getTraining()` Returns null, does not use a training set, rather uses a score function.

    Constructors in org.encog.ml.ea.train.basic with parameters of type MLDataSet
    Constructor and Description
    `TrainEA(Population thePopulation, MLDataSet trainingData)` Create a trainer for training data.

  - ### Uses of MLDataSet in org.encog.ml.factory

    Methods in org.encog.ml.factory with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `MLTrain` | GeneticFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create an annealing trainer.
    `MLTrain` | SVMFactory.`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` | LMAFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create a LMA trainer.
    `MLTrain` | NEATGAFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create an NEAT GA trainer.
    `MLTrain` | PSOFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create a PSO trainer.
    `MLTrain` | QuickPropFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create a quick propagation 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` | AnnealFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create an annealing trainer.
    `MLTrain` | SCGFactory.`create(MLMethod method, MLDataSet training, String args)` Create a SCG trainer.
    `MLTrain` | NeighborhoodSOMFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create a LMA trainer.
    `MLTrain` | BackPropFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create a backpropagation trainer.
    `MLTrain` | PNNTrainFactory.`create(MLMethod method, MLDataSet training, String args)` Create a PNN trainer.
    `MLTrain` | NelderMeadFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create a Nelder Mead trainer.
    `MLTrain` | ManhattanFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create a Manhattan trainer.
    `MLTrain` | SVMSearchFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create a SVM trainer.
    `MLTrain` | EPLGAFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create an EPL GA trainer.
    `MLTrain` | RPROPFactory.`create(MLMethod method, MLDataSet training, String argsStr)` Create a RPROP trainer.

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

    Methods in org.encog.ml.fitting.gaussian that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | TrainGaussian.`getTraining()`

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

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

    Methods in org.encog.ml.fitting.linear that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | TrainLinearRegression.`getTraining()`

    Methods in org.encog.ml.fitting.linear with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `double` | LinearRegression.`calculateError(MLDataSet data)`

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

  - ### Uses of MLDataSet in org.encog.ml.hmm

    Methods in org.encog.ml.hmm with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | MarkovGenerator.`observationSequence(int length)`

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

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

    Methods in org.encog.ml.hmm.train.bw that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | BaseBaumWelch.`getTraining()`

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

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

  - ### Uses of MLDataSet in org.encog.ml.kmeans

    Methods in org.encog.ml.kmeans that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | BasicCluster.`createDataSet()` Create a dataset from the clustered data.

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

  - ### Uses of MLDataSet in org.encog.ml.model

    Methods in org.encog.ml.model with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `double` | EncogModel.`calculateError(MLMethod method, MLDataSet data)` Calculate the error for the given method and dataset.

  - ### Uses of MLDataSet in org.encog.ml.prg

    Methods in org.encog.ml.prg with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `double` | EncogProgram.`calculateError(MLDataSet data)` Calculate the error of the ML method, given a dataset.

  - ### Uses of MLDataSet in org.encog.ml.svm

    Methods in org.encog.ml.svm with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | BasicTraining.`getTraining()`
    `MLDataSet` | MLTrain.`getTraining()`

    Methods in org.encog.ml.train with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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.
    `SimpleEarlyStoppingStrategy(MLDataSet theValidationSet)`
    `SimpleEarlyStoppingStrategy(MLDataSet theValidationSet, int theCheckFrequency)`

  - ### Uses of MLDataSet in org.encog.neural.cpn

    Methods in org.encog.neural.cpn with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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
    Modifier and Type | Interface and Description
    --- | ---
    `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
    Modifier and Type | Class and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `double` | FlatNetwork.`calculateError(MLDataSet data)` Calculate the error for this neural network.

  - ### Uses of MLDataSet in org.encog.neural.freeform

    Methods in org.encog.neural.freeform with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `double` | FreeformNetwork.`calculateError(MLDataSet data)` Calculate the error of the ML method, given a dataset.

  - ### Uses of MLDataSet in org.encog.neural.freeform.training

    Methods in org.encog.neural.freeform.training that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | FreeformPropagationTraining.`getTraining()`

    Constructors in org.encog.neural.freeform.training with parameters of type MLDataSet
    Constructor and Description
    `FreeformBackPropagation(FreeformNetwork theNetwork, MLDataSet theTraining, double theLearningRate, double theMomentum)` Construct a back propagation trainer.
    `FreeformPropagationTraining(FreeformNetwork theNetwork, MLDataSet theTraining)` Construct the trainer.
    `FreeformResilientPropagation(FreeformNetwork theNetwork, MLDataSet theTraining)` Construct the RPROP trainer, Use default intiial update and max step.
    `FreeformResilientPropagation(FreeformNetwork theNetwork, MLDataSet theTraining, double initialUpdate, double theMaxStep)` Construct the RPROP trainer.

  - ### Uses of MLDataSet in org.encog.neural.neat

    Methods in org.encog.neural.neat with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `double` | NEATPopulation.`calculateError(MLDataSet data)` Calculate the error of the ML method, given a dataset.
    `double` | NEATNetwork.`calculateError(MLDataSet data)` Calculate the error for this neural network.

  - ### Uses of MLDataSet in org.encog.neural.networks

    Methods in org.encog.neural.networks with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | TrainingJob.`getTraining()`

    Methods in org.encog.neural.networks.training.concurrent.jobs with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `void` | TrainingJob.`setTraining(MLDataSet training)`

    Constructors in org.encog.neural.networks.training.concurrent.jobs with parameters of type MLDataSet
    Constructor and Description
    `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
    Constructor and Description
    `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
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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
    Constructor and Description
    `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
    Constructor and Description
    `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
    Constructor and Description
    `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
    Constructor and Description
    `QuickPropagation(ContainsFlat network, MLDataSet training)` Construct a QPROP trainer for flat networks.
    `QuickPropagation(ContainsFlat network, MLDataSet training, double theLearningRate)` 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
    Constructor and Description
    `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
    Constructor and Description
    `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
    Constructor and Description
    `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
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | PruneIncremental.`getTraining()`

    Constructors in org.encog.neural.prune with parameters of type MLDataSet
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `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
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Class and Description
    --- | ---
    `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
    Modifier and Type | Class and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `MLTrain` | SystemActivationPlugin.`createTraining(MLMethod method, MLDataSet training, String type, String args)` Create a trainer.
    `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.

  - ### Uses of MLDataSet in org.encog.util

    Methods in org.encog.util with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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.data

    Methods in org.encog.util.data that return MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `static MLDataSet` | GenerationUtil.`generateSingleDataRange(EncogFunction task, double start, double stop, double step)`

  - ### Uses of MLDataSet in org.encog.util.error

    Methods in org.encog.util.error with parameters of type MLDataSet
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `MLDataSet` | NormalizationStorageNeuralDataSet.`getDataset()`

    Constructors in org.encog.util.normalize.target with parameters of type MLDataSet
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `static void` | ValidateNetwork.`validateMethodToData(MLMethod method, MLDataSet training)`

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