Uses of Class net.sf.tweety.machinelearning.TrainingSet

Packages that use TrainingSet
Package Description

net.sf.tweety.machinelearning

net.sf.tweety.machinelearning.svm

Uses of TrainingSet in net.sf.tweety.machinelearning

Methods in net.sf.tweety.machinelearning that return TrainingSet
Modifier and Type	Method	Description
`TrainingSet<S,T>`	TrainingSet.`getObservations(T cat)`	Returns all observations of the given category.
`static TrainingSet<DefaultObservation,DoubleCategory>`	TrainingSet.`loadLibsvmTrainingFile(java.io.File file)`	Loads a training file in LIBSVM syntax

Methods in net.sf.tweety.machinelearning with parameters of type TrainingSet
Modifier and Type	Method	Description
`ParameterSet`	GridSearchParameterLearner.`learnParameters(TrainingSet<S,T> trainingSet)`
`abstract ParameterSet`	ParameterTrainer.`learnParameters(TrainingSet<S,T> trainingSet)`	Learns the best parameters of the given trainer for the training set.
`double`	ClassificationTester.`test(Classifier classifier, TrainingSet<S,T> trainingSet)`	Measures the performance of the given classifier on the given test set, i.e.
`abstract double`	ClassificationTester.`test(Trainer<S,T> trainer, TrainingSet<S,T> trainingSet)`	This methods takes a trainer and a training set and returns the performance (in [0,1]) of the trained classifier on the training set (e.g.
`double`	CrossValidator.`test(Trainer<S,T> trainer, TrainingSet<S,T> trainingSet)`
`Classifier`	ParameterTrainer.`train(TrainingSet<S,T> trainingSet)`
`Classifier`	ParameterTrainer.`train(TrainingSet<S,T> trainingSet, ParameterSet params)`
`Classifier`	Trainer.`train(TrainingSet<S,T> trainingSet)`	Trains a classifier on the given training set.
`Classifier`	Trainer.`train(TrainingSet<S,T> trainingSet, ParameterSet params)`	Trains a classifier on the given training set with the given parameters

Uses of TrainingSet in net.sf.tweety.machinelearning.svm

Methods in net.sf.tweety.machinelearning.svm with parameters of type TrainingSet
Modifier and Type	Method	Description
`SupportVectorMachine`	MultiClassRbfTrainer.`train(TrainingSet<DefaultObservation,DoubleCategory> trainingSet)`
`SupportVectorMachine`	MultiClassRbfTrainer.`train(TrainingSet<DefaultObservation,DoubleCategory> trainingSet, ParameterSet params)`