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## Uses of Class
org.neuroph.core.learning.TrainingSet

Packages that use TrainingSet
org.neuroph.contrib.imgrec | Provides classes for image recognition with neural networks.
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.samples | Provides some basic examples of how to use Neuroph.
org.neuroph.samples.stockmarket | Provides basic example of stock market prediction with neural networks.
org.neuroph.util | Provides various utility classes for creating neural networks, type codes, parsing vectors, etc.

Uses of TrainingSet in org.neuroph.contrib.imgrec

Methods in org.neuroph.contrib.imgrec that return TrainingSet
`static TrainingSet` | `ImageRecognitionHelper.createBlackAndWhiteTrainingSet(java.util.List<java.lang.String> imageLabels, java.util.Map<java.lang.String,FractionRgbData> rgbDataMap)` Creates binary black and white training set for the specified image labels and rgb data
`static TrainingSet` | `ImageRecognitionHelper.createTrainingSet(java.util.List<java.lang.String> imageLabels, java.util.Map<java.lang.String,FractionRgbData> rgbDataMap)` Creates training set for the specified image labels and rgb data

Uses of TrainingSet in org.neuroph.core

Methods in org.neuroph.core with parameters of type TrainingSet
`void` | `NeuralNetwork.learn(TrainingSet trainingSetToLearn)` Deprecated.
`void` | `NeuralNetwork.learnInNewThread(TrainingSet trainingSetToLearn)` 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(TrainingSet trainingSetToLearn, 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
`void` | `NeuralNetwork.learnInSameThread(TrainingSet trainingSetToLearn)` Starts the learning in the current running thread to learn the specified training set, and returns from method when network is done learning
`void` | `NeuralNetwork.learnInSameThread(TrainingSet trainingSetToLearn, LearningRule learningRule)` Starts the learning with specified learning rule in the current running thread to learn the specified training set, and returns from method when network is done learning

Uses of TrainingSet in org.neuroph.core.learning

Methods in org.neuroph.core.learning that return TrainingSet
`TrainingSet` | `LearningRule.getTrainingSet()` Gets training set
`static TrainingSet` | `TrainingSet.load(java.lang.String filePath)` Loads training set from the specified file

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

Uses of TrainingSet in org.neuroph.nnet.learning

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

Uses of TrainingSet in org.neuroph.samples

Methods in org.neuroph.samples with parameters of type TrainingSet
`static void` | `PerceptronSample.testNeuralNetwork(NeuralNetwork neuralNet, TrainingSet trainingSet)` Prints network output for the each element from the specified training set.
`static void` | `XorMultiLayerPerceptronSample.testNeuralNetwork(NeuralNetwork neuralNet, TrainingSet trainingSet)` Prints network output for the each element from the specified training set.

Uses of TrainingSet in org.neuroph.samples.stockmarket

Methods in org.neuroph.samples.stockmarket that return TrainingSet
`TrainingSet` | `TrainingData.getTrainingSet()`
`static TrainingSet` | `StockTrainingSetImport.importFromArray(double[] values, int inputsCount, int outputsCount)` Creates and returns training set for stock market prediction using the provided data from array

Methods in org.neuroph.samples.stockmarket with parameters of type TrainingSet
`void` | `TrainingData.setTrainingSet(TrainingSet trainingSet)`

Uses of TrainingSet in org.neuroph.util

Methods in org.neuroph.util that return TrainingSet
`static TrainingSet` | `TrainingSetImport.importFromFile(java.lang.String filePath, int inputsCount, int outputsCount, java.lang.String separator)`

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