net.sf.tweety.machinelearning

Class GridSearchParameterLearner<S extends Observation,T extends Category>

java.lang.Object

net.sf.tweety.machinelearning.ParameterTrainer<S,T>

net.sf.tweety.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

Field Summary

Fields

Modifier and Type	Field and Description
private int	depth The depth of the recursion.
private int	partitions The number of partitions of each parameter interval.
private ClassificationTester<S,T>	tester The tester used for measuring the performance of each parameter combination.

Constructor Summary

Constructors

Constructor and 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 and Description
private ParameterSet	adjustParameterSet(ParameterSet set, int[] indices, double[] lowerBounds, double[] upperBounds) Determine for all parameters of the set a new value, determined by partitioning [lowerBound,upperBound] into this.partitions number of sub intervals and then taking the center point of the partition no.
private boolean	increment(int[] indices, int maxIdx) Increments the given array of indices, e.g.
ParameterSet	learnParameters(TrainingSet<S,T> trainingSet) Learns the best parameters of the given trainer for the training set.

Methods inherited from class net.sf.tweety.machinelearning.ParameterTrainer

getParameterSet, getTrainer, setParameterSet, train, train

Methods inherited from class java.lang.Object

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

Field Detail

depth

private int depth

The depth of the recursion.

partitions

private int partitions

The number of partitions of each parameter interval.

tester

private ClassificationTester<S extends Observation,T extends Category> tester

The tester used for measuring the performance of each parameter combination.

Constructor Detail

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 Detail

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.

adjustParameterSet

private ParameterSet adjustParameterSet(ParameterSet set,
                                        int[] indices,
                                        double[] lowerBounds,
                                        double[] upperBounds)

Determine for all parameters of the set a new value, determined by partitioning [lowerBound,upperBound] into this.partitions number of sub intervals and then taking the center point of the partition no. idx.

Parameters:

set - a parameter set

indices - indices

lowerBounds - the lower bounds

upperBounds - the upper bounds

Returns:

a new parameter set

increment

private boolean increment(int[] indices,
                          int maxIdx)

Increments the given array of indices, e.g. (for maxIdx=5) given [0,0,0,0] it returns [1,0,0,0], given [4,2,1,4] it returns [5,2,1,4], given [5,2,1,4] it returns [0,3,1,4], given [5,5,1,4] it returns [0,0,2,4], etc. It returns true iff an overflow occurs, e.g. if [5,5,5,5] is to be incremented.

Parameters:

indices - an array of ints.

maxIdx - the max index.

Returns:

"true" iff an overflow occurs