keel.Algorithms.Instance_Generation.HYB

Class SVMSEL

java.lang.Object

keel.Algorithms.Instance_Generation.Basic.PrototypeGenerator

keel.Algorithms.Instance_Generation.HYB.SVMSEL

public class SVMSEL
extends PrototypeGenerator

SVM process of selection of prototype set.

Author:

Salvador García López, adapted by Diego J. Romero López

Field Summary

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

algorithmName, generatedDataSet, SEED, seedDefaultValueList, trainingDataSet

Constructor Summary

Constructors

Constructor and Description
SVMSEL(PrototypeSet _trainingDataSet, java.lang.String kernelType) Performs an selection of the training data set using SVM.
SVMSEL(PrototypeSet _trainingDataSet, java.lang.String kernelType, double C, double eps, int degree, double gamma, double nu, double p, int shrinking) Performs an selection of the training data set using SVM.

Method Summary

Modifier and Type	Method and Description
PrototypeSet	doSVMSelection() Executes the SVM prototype selection.
PrototypeSet	reduceSet() Reduction of the original prototype set by the SVM.

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

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

Methods inherited from class java.lang.Object

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

Constructor Detail

SVMSEL

public SVMSEL(PrototypeSet _trainingDataSet,
              java.lang.String kernelType,
              double C,
              double eps,
              int degree,
              double gamma,
              double nu,
              double p,
              int shrinking)

Performs an selection of the training data set using SVM.

Parameters:

_trainingDataSet - training dataset

kernelType - {LINEAR, POLY, RBF, SIGMOID} linear: u'*v; polynomial: (gamma*u'*v + coef0)^degree; radial basis function: exp(-gamma*|u-v|^2); sigmoid: tanh(gamma*u'*v + coef0)

C - Parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1).

eps - Epsilon in loss function of epsilon-SVR (default 0.1)

degree - Degree in kernel function (default 3)

gamma - Gamma in kernel function (default 1/k)

nu - Parameter nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5)

p - P-parameter of the SVM.

shrinking - Whether to use the shrinking heuristics, 0 or 1 (default 1)

SVMSEL

public SVMSEL(PrototypeSet _trainingDataSet,
              java.lang.String kernelType)

Performs an selection of the training data set using SVM.

Parameters:

_trainingDataSet - training dataset.

kernelType - {LINEAR, POLY, RBF, SIGMOID} linear: u'*v; polynomial: (gamma*u'*v + coef0)^degree; radial basis function: exp(-gamma*|u-v|^2); sigmoid: tanh(gamma*u'*v + coef0)

Method Detail

doSVMSelection

public PrototypeSet doSVMSelection()

Executes the SVM prototype selection.

Returns:

Selected prototypes by SVM method.

reduceSet

public PrototypeSet reduceSet()

Reduction of the original prototype set by the SVM.

Overrides:

reduceSet in class PrototypeGenerator

Returns:

Prototypes selected by SVM.