Package | Description |
---|---|
net.sf.tweety.machinelearning | |
net.sf.tweety.machinelearning.svm |
Modifier and Type | Method and 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
|
Modifier and Type | Method and 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 |
Trainer.train(TrainingSet<S,T> trainingSet)
Trains a classifier on the given training set.
|
Classifier |
ParameterTrainer.train(TrainingSet<S,T> trainingSet) |
Classifier |
Trainer.train(TrainingSet<S,T> trainingSet,
ParameterSet params)
Trains a classifier on the given training set with the given parameters
|
Classifier |
ParameterTrainer.train(TrainingSet<S,T> trainingSet,
ParameterSet params) |
Modifier and Type | Method and Description |
---|---|
SupportVectorMachine |
MultiClassRbfTrainer.train(TrainingSet<DefaultObservation,DoubleCategory> trainingSet) |
SupportVectorMachine |
MultiClassRbfTrainer.train(TrainingSet<DefaultObservation,DoubleCategory> trainingSet,
ParameterSet params) |