keel.Algorithms.Associative_Classification.ClassifierFuzzyFCRA

Class Population

java.lang.Object

keel.Algorithms.Associative_Classification.ClassifierFuzzyFCRA.Population

public class Population
extends java.lang.Object

This class contains the population for the genetic algorithm

Since:

JDK1.5

Version:

1.2

Author:

Written by Jesus Alcalá (University of Granada) 09/02/2010

Constructor Summary

Constructors

Constructor and Description
Population() Default Constructor
Population(myDataset train, DataBase dataBase, int size, double crossProb, double mutProb, int lengthSC, double wCAR, double wV, double n1, double n2, int Jmax, Apriori apriori) Constructor with parameters

Method Summary

Modifier and Type	Method and Description
boolean	BETTER(double a, double b) Maximization
void	Generation(int n_Generations) Main procedure of the GA
double	getBestMinFC() It returns the best minimum confidence
double	getBestMinFS() It returns the best minimum support
RuleBase	getBestRB() It returns the best RB found so far

Methods inherited from class java.lang.Object

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

Constructor Detail

Population

public Population()

Default Constructor

Population

public Population(myDataset train,
                  DataBase dataBase,
                  int size,
                  double crossProb,
                  double mutProb,
                  int lengthSC,
                  double wCAR,
                  double wV,
                  double n1,
                  double n2,
                  int Jmax,
                  Apriori apriori)

Constructor with parameters

Parameters:

train - myDataset training set

dataBase - DataBase dataBase

size - int population size

crossProb - double crossover probability

mutProb - double mutation probability

lengthSC - int total length of the individuals

wCAR - double relative weight of the classification accuracy rate

wV - double relative weight of the number of fuzzy rules

n1 - double learning rate (Nozaki method)

n2 - double learning rate (Nozaki method)

Jmax - int number of iterations (Nozaki method)

apriori - Apriori an Apriori objects

Method Detail

BETTER

public boolean BETTER(double a,
                      double b)

Maximization

Parameters:

a - int first number

b - int second number

Returns:

boolean true if a is greater than b

Generation

public void Generation(int n_Generations)

Main procedure of the GA

Parameters:

n_Generations - int number of generations

getBestRB

public RuleBase getBestRB()

It returns the best RB found so far

Returns:

RuleBase the best RB found so far

getBestMinFS

public double getBestMinFS()

It returns the best minimum support

Returns:

double the best minimum support found so far

getBestMinFC

public double getBestMinFC()

It returns the best minimum confidence

Returns:

double the best minimum confidence found so far