keel.Algorithms.UnsupervisedLearning.AssociationRules.FuzzyRuleLearning.GeneticFuzzyAprioriDC

Class GeneticFuzzyAprioriDCProcess

java.lang.Object

keel.Algorithms.UnsupervisedLearning.AssociationRules.FuzzyRuleLearning.GeneticFuzzyAprioriDC.GeneticFuzzyAprioriDCProcess

public class GeneticFuzzyAprioriDCProcess
extends java.lang.Object

It provides the implementation of the algorithm to be run in a process.

Since:

JDK1.6

Version:

1.0

Author:

Written by Alvaro Lopez

Constructor Summary

Constructors

Constructor and Description
GeneticFuzzyAprioriDCProcess(myDataset dataset, int nEvaluations, int popSize, double pm, double pc, double d, int nFuzzyRegionsForNumericAttributes, boolean useMaxForOneFrequentItemsets, double minSupport, double minConfidence) It creates a new process for the algorithm by setting up its parameters

Method Summary

Modifier and Type	Method and Description
java.util.ArrayList<FuzzyAttribute>	getFuzzyAttributes() It returns the mined fuzzy attributes once the genetic learning has been accomplished
java.lang.String	getGeneticLearningLog() It returns the XML string representing the genetic learning log
int	getNumberOfOneFrequentItemsets() It returns the number of 1-Frequent Itemsets
java.util.ArrayList<AssociationRule>	getRulesSet() It returns a rules set once the algorithm has been carried out
void	printReport(java.util.ArrayList<AssociationRule> rules) It prints out on screen relevant information regarding the mined association rules
void	run() It runs the algorithm for mining association rules

Methods inherited from class java.lang.Object

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

Constructor Detail

GeneticFuzzyAprioriDCProcess

public GeneticFuzzyAprioriDCProcess(myDataset dataset,
                                    int nEvaluations,
                                    int popSize,
                                    double pm,
                                    double pc,
                                    double d,
                                    int nFuzzyRegionsForNumericAttributes,
                                    boolean useMaxForOneFrequentItemsets,
                                    double minSupport,
                                    double minConfidence)

It creates a new process for the algorithm by setting up its parameters

Parameters:

dataset - The instance of the dataset for dealing with its records

nEvaluations - The maximum number of evaluations to accomplish before terminating the genetic learning

popSize - The maximum size of population to handle after each generation

pm - The probability of the mutation operator

pc - The probability of the crossover operator

d - The parameter which is used while executing the crossover operator

nFuzzyRegionsForNumericAttributes - The number of fuzzy regions with which numeric attributes are evaluated

useMaxForOneFrequentItemsets - It indicates whether the max operator must be used while discovering 1-Frequent Itemsets

minSupport - The user-specified minimum support for the mined association rules

minConfidence - The user-specified minimum confidence for the mined association rules

Method Detail

run

public void run()

It runs the algorithm for mining association rules

getRulesSet

public java.util.ArrayList<AssociationRule> getRulesSet()

It returns a rules set once the algorithm has been carried out

Returns:

An array of association rules having both minimum confidence and support

printReport

public void printReport(java.util.ArrayList<AssociationRule> rules)

It prints out on screen relevant information regarding the mined association rules

Parameters:

rules - The array of association rules from which gathering relevant information

getNumberOfOneFrequentItemsets

public int getNumberOfOneFrequentItemsets()

It returns the number of 1-Frequent Itemsets

Returns:

A value representing the number of 1-Frequent Itemsets

getGeneticLearningLog

public java.lang.String getGeneticLearningLog()

It returns the XML string representing the genetic learning log

Returns:

A string containing the genetic learning text

getFuzzyAttributes

public java.util.ArrayList<FuzzyAttribute> getFuzzyAttributes()

It returns the mined fuzzy attributes once the genetic learning has been accomplished

Returns:

An array representing the mined fuzzy attributes