keel.Algorithms.Semi_Supervised_Learning.CoBC

Class CoBCGenerator

java.lang.Object

keel.Algorithms.Semi_Supervised_Learning.Basic.PrototypeGenerator

keel.Algorithms.Semi_Supervised_Learning.CoBC.CoBCGenerator

public class CoBCGenerator
extends PrototypeGenerator

This class implements the Co-traning wrapper. You can use: Knn, C4.5, SMO as classifiers.

Author:

Isaac Triguero

Field Summary

Fields

Modifier and Type	Field and Description
protected int	numberOfClass Number of classes.
protected int	numberOfClassifiers Number of classifiers considered.
protected int	numberOfPrototypes Number of prototypes.

Fields inherited from class keel.Algorithms.Semi_Supervised_Learning.Basic.PrototypeGenerator

algorithmName, generatedDataSet, Instancetest, Instancetrain, SEED, seedDefaultValueList, testDataSet, trainingDataSet, transductiveDataSet

Constructor Summary

Constructors

Constructor and Description
CoBCGenerator(PrototypeSet _trainingDataSet, int neigbors, int poblacion, int perc, int iteraciones, double c1, double c2, double vmax, double wstart, double wend) Build a new CoBCGenerator Algorithm
CoBCGenerator(PrototypeSet t, PrototypeSet unlabeled, PrototypeSet test, Parameters parameters) Build a new CoBCGenerator Algorithm

Method Summary

Modifier and Type	Method and Description
Pair<PrototypeSet,PrototypeSet>	applyAlgorithm() Apply the CoBCGenerator method with 3 classifiers: C45, NB, and 3NN
double[]	clasificar(PrototypeSet[] train, PrototypeSet test) Classify the instances given.
double[]	EnsembleLearn(PrototypeSet[] Labeled, PrototypeSet test) Builds the ensemble with the labeled dataset and classifies the test instances.
void	getSolicitaGarbageColector() Asks for the garbage collector
static void	main(java.lang.String[] args) General main for all the prototoype generators Arguments: 0: Filename with the training data set to be condensed. 1: Filename which contains the test data set. 3: Seed of the random number generator.

Methods inherited from class keel.Algorithms.Semi_Supervised_Learning.Basic.PrototypeGenerator

absoluteAccuracy, absoluteAccuracyAndError, absoluteAccuracyKNN, accuracy, accuracy2, desordenar_vector_sin, desordenar_vector, execute, generateReducedDataSet, getResultingAccuracy, getResultsOfAccuracy, getSeed, getSetSizeFromPercentage, getSetSizeFromPercentage, getTime, inic_vector_sin, inic_vector, saveResultsOfAccuracyIn, selecRandomSet, setInstanceTest, setInstanceTrain, setSeed

Methods inherited from class java.lang.Object

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

Field Detail

numberOfClassifiers

protected int numberOfClassifiers

Number of classifiers considered.

numberOfPrototypes

protected int numberOfPrototypes

Number of prototypes.

numberOfClass

protected int numberOfClass

Number of classes.

Constructor Detail

CoBCGenerator

public CoBCGenerator(PrototypeSet _trainingDataSet,
                     int neigbors,
                     int poblacion,
                     int perc,
                     int iteraciones,
                     double c1,
                     double c2,
                     double vmax,
                     double wstart,
                     double wend)

Build a new CoBCGenerator Algorithm

Parameters:

_trainingDataSet - Original prototype set to be reduced.

neigbors - number of neighbours considered. (not used)

poblacion - population size. (not used)

perc - Reduction percentage of the prototype set.

iteraciones - number of iterations. (not used)

wend - ending w value. (not used)

c1 - class 1 value. (not used)

vmax - maximum v value. (not used)

c2 - class 2 value. (not used)

wstart - starting w value. (not used)

CoBCGenerator

public CoBCGenerator(PrototypeSet t,
                     PrototypeSet unlabeled,
                     PrototypeSet test,
                     Parameters parameters)

Build a new CoBCGenerator Algorithm

Parameters:

t - Original prototype set to be reduced.

unlabeled - Original unlabeled prototype set for SSL.

test - Origital test prototype set.

parameters - Parameters of the algorithm (only % of reduced set).

Method Detail

clasificar

public double[] clasificar(PrototypeSet[] train,
                           PrototypeSet test)
                    throws java.lang.Exception

Classify the instances given.

Parameters:

train - Training instances partitions to build the models.

test - Test instances set to classify.

Returns:

the predicted classes for test instances.

Throws:

java.lang.Exception

EnsembleLearn

public double[] EnsembleLearn(PrototypeSet[] Labeled,
                              PrototypeSet test)
                       throws java.lang.Exception

Builds the ensemble with the labeled dataset and classifies the test instances.

Parameters:

Labeled - Labeled dataset to build the ensemble.

test - Test dataset to classify.

Returns:

predicted classes for the test instances.

Throws:

java.lang.Exception - if the models can not be built.

getSolicitaGarbageColector

public void getSolicitaGarbageColector()

Asks for the garbage collector

applyAlgorithm

public Pair<PrototypeSet,PrototypeSet> applyAlgorithm()
                                               throws java.lang.Exception

Apply the CoBCGenerator method with 3 classifiers: C45, NB, and 3NN

Overrides:

applyAlgorithm in class PrototypeGenerator

Returns:

Pair of prototypes set (transductive, test)

Throws:

java.lang.Exception - if the algorithm can not be applied.

main

public static void main(java.lang.String[] args)

General main for all the prototoype generators Arguments: 0: Filename with the training data set to be condensed. 1: Filename which contains the test data set. 3: Seed of the random number generator. Always. **************************

Parameters:

args - Arguments of the main function.