S - the type of observations.T - the type of categories.public class GridSearchParameterLearner<S extends Observation,T extends Category> extends ParameterTrainer<S,T>
partitions
number of partitions. For each partition of each parameter the border points are chosen and a new
classifier is learned with given parameter combination. From all combinations the combination
where the classifier performs best is chosen. If depth > 1, the process is iterated: after selecting
the best interval combination of the parameters, these intervals are again divided and the process
is repeated depth many times.| Constructor and Description |
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GridSearchParameterLearner(Trainer<S,T> trainer,
ClassificationTester<S,T> tester,
int depth,
int partitions)
Creates a new grid-search parameter learner with the given arguments.
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| Modifier and Type | Method and Description |
|---|---|
ParameterSet |
learnParameters(TrainingSet<S,T> trainingSet)
Learns the best parameters of the given trainer for the training set.
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getParameterSet, getTrainer, setParameterSet, train, trainpublic GridSearchParameterLearner(Trainer<S,T> trainer, ClassificationTester<S,T> tester, int depth, int partitions)
trainer - some trainer.tester - some classification tester for measuring performance.depth - the depth of the recursion.partitions - the number of partitions.public ParameterSet learnParameters(TrainingSet<S,T> trainingSet)
ParameterTrainerlearnParameters in class ParameterTrainer<S extends Observation,T extends Category>trainingSet - a training setCopyright © 2018. All rights reserved.