keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Fuzzy_Ish_Hybrid

Class Rule

java.lang.Object

keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Fuzzy_Ish_Hybrid.Rule

All Implemented Interfaces:

java.lang.Comparable

public class Rule
extends java.lang.Object
implements java.lang.Comparable

Title: Rule

Description: Codifies a Fuzzy Rule

Copyright: KEEL Copyright (c) 2008

Company: KEEL

Since:

JDK1.5

Version:

1.5

Author:

Written by Alberto Fernández (University of Granada) 29/10/2007, Modified by Alberto Fernández (University of Granada) 03/09/2009

Constructor Summary

Constructors

Constructor and Description
Rule(DataBase dataBase, int compatibilityType, boolean[] nominals) Constructor with parameters
Rule(Rule r) Copy Constructor

Method Summary

Modifier and Type	Method and Description
void	assignConsequent(myDataset train, int ruleWeight) It assigns the rule Weigth
void	buildHeuristic(myDataset train, int example, double p_DC) Builds a new rule from a heuristic function
Rule	clone() It carries out a copy of the current rule
int	compareTo(java.lang.Object a) Compares the fitness of two rules for the ordering procedure
double	compatibility(double[] example) Computes the compatibility of a given example with the rule.
void	computeConsequent(myDataset train) Procedure to compute the best consequent for a given rule
void	mutate(myDataset train, double prob_mut) Mutatation Operator.
void	setClass(int clas) Sets the class for the rule

Methods inherited from class java.lang.Object

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

Constructor Detail

Rule

public Rule(Rule r)

Copy Constructor

Parameters:

r - Rule the rule to be copied

Rule

public Rule(DataBase dataBase,
            int compatibilityType,
            boolean[] nominals)

Constructor with parameters

Parameters:

dataBase - DataBase the DB

compatibilityType - int a code for the compatibility degre computation

nominals - array that indicates the possible nominal attributes of the data-set

Method Detail

buildHeuristic

public void buildHeuristic(myDataset train,
                           int example,
                           double p_DC)

Builds a new rule from a heuristic function

Parameters:

train - myDataset the tranning set

example - int an example for building the rule

p_DC - double the don't care probability

computeConsequent

public void computeConsequent(myDataset train)

Procedure to compute the best consequent for a given rule

Parameters:

train - myDataset the tranning set

setClass

public void setClass(int clas)

Sets the class for the rule

Parameters:

clas - int the class id

assignConsequent

public void assignConsequent(myDataset train,
                             int ruleWeight)

It assigns the rule Weigth

Parameters:

train - myDataset trainnig set

ruleWeight - int code for selecting the rule weight heuristic computation

compatibility

public double compatibility(double[] example)

Computes the compatibility of a given example with the rule.

Parameters:

example - example to be tested.

Returns:

the compatibility of a given example

clone

public Rule clone()

It carries out a copy of the current rule

Overrides:

clone in class java.lang.Object

Returns:

Rule an exact copy of the rule

mutate

public void mutate(myDataset train,
                   double prob_mut)

Mutatation Operator. It assigns a random new label for each condition according to the mutation probability.

Parameters:

train - myDataset trainnig set

prob_mut - double mutation probability

compareTo

public int compareTo(java.lang.Object a)

Compares the fitness of two rules for the ordering procedure

Specified by:

compareTo in interface java.lang.Comparable

Parameters:

a - Object a Rule

Returns:

int -1 if the current rule is worst than the one that is compared, 1 for the contrary case and 0 if they are equal.