keel.Algorithms.Instance_Generation.DEGL

Class DEGLGenerator

java.lang.Object

keel.Algorithms.Instance_Generation.Basic.PrototypeGenerator

keel.Algorithms.Instance_Generation.DEGL.DEGLGenerator

public class DEGLGenerator
extends PrototypeGenerator

DEGL.java DEGL prototype generator.

Version:

1.0

Author:

Isaac Triguero

Field Summary

Fields

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

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

algorithmName, generatedDataSet, SEED, seedDefaultValueList, trainingDataSet

Constructor Summary

Constructors

Constructor and Description
DEGLGenerator(PrototypeSet _trainingDataSet, int neigbors, int poblacion, int perc, int iteraciones, double F, double CR, int strg) Build a new DEGLGenerator Algorithm
DEGLGenerator(PrototypeSet t, Parameters parameters) Build a new DEGLGenerator Algorithm

Method Summary

Modifier and Type	Method and Description
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.
PrototypeSet	mutant(PrototypeSet[] population, int actual, int bestFitnessIndex, int bestNeighboor) Mutation operator.
PrototypeSet	reduceSet() Generate a reduced prototype set by the DEGLGenerator method.

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, saveResultsOfAccuracyIn, saveResultsOfAccuracyIn, selecRandomSet, setSeed, showResultsOfAccuracy, showResultsOfAccuracy

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 considered

numberOfClass

protected int numberOfClass

Number of classes considered

Constructor Detail

DEGLGenerator

public DEGLGenerator(PrototypeSet _trainingDataSet,
                     int neigbors,
                     int poblacion,
                     int perc,
                     int iteraciones,
                     double F,
                     double CR,
                     int strg)

Build a new DEGLGenerator Algorithm

Parameters:

_trainingDataSet - training dataset to build the model.

neigbors - Number of neighbors to consider

poblacion - population size.

F - Scaling factor

iteraciones - maximum number of iterations.

perc - particle size.

CR - cross rate.

strg - strategy of the algorithm (from 1 to 5)

DEGLGenerator

public DEGLGenerator(PrototypeSet t,
                     Parameters parameters)

Build a new DEGLGenerator Algorithm

Parameters:

t - Original prototype set to be reduced.

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

Method Detail

mutant

public PrototypeSet mutant(PrototypeSet[] population,
                           int actual,
                           int bestFitnessIndex,
                           int bestNeighboor)

Mutation operator.

Parameters:

population - set of populations.

actual - actual population.

bestFitnessIndex - best fitness index.

bestNeighboor - best neighbour index.

Returns:

prototype set after the mutation operator.

reduceSet

public PrototypeSet reduceSet()

Generate a reduced prototype set by the DEGLGenerator method.

Overrides:

reduceSet in class PrototypeGenerator

Returns:

Reduced set by DEGLGenerator's method.

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. ************************** 4: .Number of neighbors 5: Swarm Size 6: Particle Size 7: Max Iter 8: C1 9: c2 10: vmax 11: wstart 12: wend

Parameters:

args - Arguments of the main function.