keel.Algorithms.Semi_Supervised_Learning.C45SSL

Class C45SSLGenerator

java.lang.Object

keel.Algorithms.Semi_Supervised_Learning.Basic.PrototypeGenerator

keel.Algorithms.Semi_Supervised_Learning.C45SSL.C45SSLGenerator

public class C45SSLGenerator
extends PrototypeGenerator

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

Author:

triguero

Field Summary

Fields

Modifier and Type	Field and Description
protected int	numberOfClass Number of classes.
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
C45SSLGenerator(PrototypeSet _trainingDataSet, int neigbors, int poblacion, int perc, int iteraciones, double c1, double c2, double vmax, double wstart, double wend) Build a new C45SSLGenerator Algorithm
C45SSLGenerator(PrototypeSet t, PrototypeSet unlabeled, PrototypeSet test, Parameters parameters) Build a new C45SSLGenerator Algorithm

Method Summary

Modifier and Type	Method and Description
Pair<PrototypeSet,PrototypeSet>	applyAlgorithm() Apply the C45SSLGenerator method.
int[]	applyC45(PrototypeSet labeled, PrototypeSet unlabeled) Applies the C4.5 algorithm for the dataset given.
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

numberOfPrototypes

protected int numberOfPrototypes

Number of prototypes.

numberOfClass

protected int numberOfClass

Number of classes.

Constructor Detail

C45SSLGenerator

public C45SSLGenerator(PrototypeSet _trainingDataSet,
                       int neigbors,
                       int poblacion,
                       int perc,
                       int iteraciones,
                       double c1,
                       double c2,
                       double vmax,
                       double wstart,
                       double wend)

Build a new C45SSLGenerator 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)

C45SSLGenerator

public C45SSLGenerator(PrototypeSet t,
                       PrototypeSet unlabeled,
                       PrototypeSet test,
                       Parameters parameters)

Build a new C45SSLGenerator 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

applyC45

public int[] applyC45(PrototypeSet labeled,
                      PrototypeSet unlabeled)
               throws java.lang.Exception

Applies the C4.5 algorithm for the dataset given.

Parameters:

labeled - labeled dataset to build the model.

unlabeled - unlabeled dataset to obtain their predicted classes.

Returns:

predicted classes for the unlabeled dataset.

Throws:

java.lang.Exception

applyAlgorithm

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

Apply the C45SSLGenerator method.

Overrides:

applyAlgorithm in class PrototypeGenerator

Returns:

transductive test sets.

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.