Package org.tweetyproject.machinelearning

Class CrossValidator<S extends Observation,T extends Category>

java.lang.Object

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

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

Type Parameters:

S - the type of observation

T - the type of category

public class CrossValidator<S extends Observation,T extends Category>
extends ClassificationTester<S,T>

Performs cross-validation in a classifier, i.e. it divides a given training set into N parts (more precisely, for each category present in the training set, the observations belonging each category are partitioned into N parts), for each i=1,...,N trains a classifier on the union of all parts except i, and measures the performance on part i. The final performance measure is the average on these N rounds.

Author:

Matthias Thimm

Constructor Summary

Constructors

Constructor	Description
CrossValidator(int fold)	Creates a new cross-validator with the given number of partitions.

Method Summary

Modifier and Type	Method	Description
double	test(Trainer<S,T> trainer, TrainingSet<S,T> trainingSet)	This method takes a trainer and a training set and returns the performance (in the range [0,1]) of the trained classifier on the training set (e.g.

Methods inherited from class org.tweetyproject.machinelearning.ClassificationTester

test

Methods inherited from class java.lang.Object

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

Constructor Details

CrossValidator

public CrossValidator(int fold)

Creates a new cross-validator with the given number of partitions.

Parameters:

fold - the number of partitions.

Method Details

test

public double test(Trainer<S,T> trainer,
 TrainingSet<S,T> trainingSet)

Description copied from class: ClassificationTester

This method takes a trainer and a training set and returns the performance (in the range [0,1]) of the trained classifier on the training set (e.g. using cross-validation). The larger the value, the better the trained classifier.

Specified by:

test in class ClassificationTester<S extends Observation,T extends Category>

Parameters:

trainer - some trainer

trainingSet - some training set

Returns:

the performance of the trained classifier