Package org.tweetyproject.machinelearning

Class GridSearchParameterLearner<S extends Observation,T extends Category>

java.lang.Object

org.tweetyproject.machinelearning.ParameterTrainer<S,T>

org.tweetyproject.machinelearning.GridSearchParameterLearner<S,T>

Type Parameters:

S - the type of observations.

T - the type of categories.

All Implemented Interfaces:

Trainer<S,T>

public class GridSearchParameterLearner<S extends Observation,T extends Category>
extends ParameterTrainer<S,T>

A grid-search approach for learning parameters. For each parameter with I=[l,u] being the boundaries for the parameter value of a given trainer, I is divided into 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.

Author:

Matthias Thimm

Constructor Summary

Constructors

Constructor	Description
GridSearchParameterLearner(Trainer<S,T> trainer, ClassificationTester<S,T> tester, int depth, int partitions)	Creates a new grid-search parameter learner with the given arguments.

Method Summary

Modifier and Type	Method	Description
ParameterSet	learnParameters(TrainingSet<S,T> trainingSet)	Learns the best parameters of the given trainer for the training set.

Methods inherited from class org.tweetyproject.machinelearning.ParameterTrainer

getParameterSet, setParameterSet, train, train

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

GridSearchParameterLearner

public GridSearchParameterLearner(Trainer<S,T> trainer,
 ClassificationTester<S,T> tester,
 int depth,
 int partitions)

Creates a new grid-search parameter learner with the given arguments.

Parameters:

trainer - some trainer.

tester - some classification tester for measuring performance.

depth - the depth of the recursion.

partitions - the number of partitions.

Method Details

learnParameters

public ParameterSet learnParameters(TrainingSet<S,T> trainingSet)

Description copied from class: ParameterTrainer

Learns the best parameters of the given trainer for the training set.

Specified by:

learnParameters in class ParameterTrainer<S extends Observation,T extends Category>

Parameters:

trainingSet - a training set

Returns:

the best parameters for the training set.