Uses of Class
org.neuroph.core.learning.DataSet

Packages that use DataSet
org.neuroph.core Provides base classes and basic building components for neural networks. 
org.neuroph.core.learning Provides base classes for neural network learning algorithms. 
org.neuroph.nnet.learning Provides implementations of specific neural network learning algorithms. 
org.neuroph.util Provides various utility classes for creating neural networks, type codes, parsing vectors, etc. 
org.neuroph.util.norm Provides data normalization techniques 
 

Uses of DataSet in org.neuroph.core
 

Methods in org.neuroph.core with parameters of type DataSet
 void NeuralNetwork.learn(DataSet trainingSet)
          Learn the specified training set
 void NeuralNetwork.learn(DataSet trainingSet, LearningRule learningRule)
          Learn the specified training set, using specified learning rule
 void NeuralNetwork.learnInNewThread(DataSet trainingSet)
          Starts learning in a new thread to learn the specified training set, and immediately returns from method to the current thread execution
 void NeuralNetwork.learnInNewThread(DataSet trainingSet, LearningRule learningRule)
          Starts learning with specified learning rule in new thread to learn the specified training set, and immediately returns from method to the current thread execution
 

Uses of DataSet in org.neuroph.core.learning
 

Methods in org.neuroph.core.learning that return DataSet
static DataSet DataSet.createFromFile(String filePath, int inputsCount, int outputsCount, String delimiter)
           
 DataSet[] DataSet.createTrainingAndTestSubsets(int trainSetPercent, int testSetPercent)
          Returns output vector size of training elements in this training set This method is implementation of EngineIndexableSet interface, and it is added to provide compatibility with Encog data sets and FlatNetwork
 DataSet LearningRule.getTrainingSet()
          Gets training set
static DataSet DataSet.load(String filePath)
          Loads training set from the specified file
 

Methods in org.neuroph.core.learning with parameters of type DataSet
 void UnsupervisedLearning.doLearningEpoch(DataSet trainingSet)
          This method does one learning epoch for the unsupervised learning rules.
 void SupervisedLearning.doLearningEpoch(DataSet trainingSet)
          This method implements basic logic for one learning epoch for the supervised learning algorithms.
abstract  void IterativeLearning.doLearningEpoch(DataSet trainingSet)
          Override this method to implement specific learning epoch - one learning iteration, one pass through whole training set
 void IterativeLearning.doOneLearningIteration(DataSet trainingSet)
          Runs one learning iteration for the specified training set and notfies observers.
abstract  void LearningRule.learn(DataSet trainingSet)
          Override this method to implement specific learning procedures
 void IterativeLearning.learn(DataSet trainingSet)
           
 void SupervisedLearning.learn(DataSet trainingSet, double maxError)
          Trains network for the specified training set and number of iterations
 void SupervisedLearning.learn(DataSet trainingSet, double maxError, int maxIterations)
          Trains network for the specified training set and number of iterations
 void IterativeLearning.learn(DataSet trainingSet, int maxIterations)
          Trains network for the specified training set and number of iterations
 void LearningRule.setTrainingSet(DataSet trainingSet)
          Sets training set for this learning rule
 

Uses of DataSet in org.neuroph.nnet.learning
 

Methods in org.neuroph.nnet.learning with parameters of type DataSet
 void UnsupervisedHebbianLearning.doLearningEpoch(DataSet trainingSet)
          This method does one learning epoch for the unsupervised learning rules.
 void SimulatedAnnealingLearning.doLearningEpoch(DataSet trainingSet)
          Perform one simulated annealing epoch.
 void DynamicBackPropagation.doLearningEpoch(DataSet trainingSet)
           
 void CompetitiveLearning.doLearningEpoch(DataSet trainingSet)
          This method does one learning epoch for the unsupervised learning rules.
 void KohonenLearning.learn(DataSet trainingSet)
           
 void HopfieldLearning.learn(DataSet trainingSet)
          Calculates weights for the hopfield net to learn the specified training set
 

Uses of DataSet in org.neuroph.util
 

Methods in org.neuroph.util that return DataSet
static DataSet TrainingSetImport.importFromFile(String filePath, int inputsCount, int outputsCount, String separator)
           
 

Uses of DataSet in org.neuroph.util.norm
 

Methods in org.neuroph.util.norm with parameters of type DataSet
 void Normalizer.normalize(DataSet dataSet)
          Normalize specified training set
 void MaxNormalizer.normalize(DataSet dataSet)
           
 void MaxMinNormalizer.normalize(DataSet dataSet)
           
 void DecimalScaleNormalizer.normalize(DataSet dataSet)
           
 



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