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.normalize.target
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	RPROPFactory.create(MLMethod method, MLDataSet training, String argsStr) Create a RPROP trainer.
MLTrain	BackPropFactory.create(MLMethod method, MLDataSet training, String argsStr) Create a backpropagation trainer.
MLTrain	ManhattanFactory.create(MLMethod method, MLDataSet training, String argsStr) Create a Manhattan trainer.
MLTrain	GeneticFactory.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	SVMFactory.create(MLMethod method, MLDataSet training, String argsStr) Create a SVM trainer.
MLTrain	SVMSearchFactory.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	PNNTrainFactory.create(MLMethod method, MLDataSet training, String args) Create a PNN trainer.
MLTrain	LMAFactory.create(MLMethod method, MLDataSet training, String argsStr) Create a LMA trainer.
MLTrain	ClusterSOMFactory.create(MLMethod method, MLDataSet training, String argsStr) Create a cluster SOM trainer.
MLTrain	QuickPropFactory.create(MLMethod method, MLDataSet training, String argsStr) Create a quick propagation trainer.
MLTrain	RBFSVDFactory.create(MLMethod method, MLDataSet training, String args) Create a RBF-SVD trainer.
MLTrain	NeighborhoodSOMFactory.create(MLMethod method, MLDataSet training, String argsStr) Create a LMA 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	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.
MLTrain	SystemTrainingPlugin.createTraining(MLMethod method, MLDataSet training, String type, String args)

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.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)