public class AlcalaetalProcess
extends java.lang.Object
It provides the implementation of the algorithm to be run in a process
Constructor and Description |
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AlcalaetalProcess(myDataset dataset,
int nEvaluations,
int popSize,
int nBitsGene,
double phi,
double d,
int nFuzzyRegionsForNumericAttributes,
boolean useMaxForOneFrequentItemsets,
double minSupport,
double minConfidence)
It creates a new process for the algorithm by setting up its parameters
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Modifier and Type | Method and Description |
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java.util.ArrayList<FuzzyAttribute> |
getAdjustedFuzzyAttributes()
It returns the mined fuzzy attributes once the genetic learning has been accomplished
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java.lang.String |
getGeneticLearningLog()
It returns the XML string representing the genetic learning log
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int |
getNumberOfOneFrequentItemsets()
It returns the number of 1-Frequent Itemsets
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java.util.ArrayList<AssociationRule> |
getRulesSet()
It returns a rules set once the algorithm has been carried out
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java.util.ArrayList<FuzzyAttribute> |
getUniformFuzzyAttributes()
It returns the uniform fuzzy attributes before running the genetic learning process
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void |
printReport(java.util.ArrayList<AssociationRule> rules)
It prints out on screen relevant information regarding the mined association rules
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void |
run()
It runs the algorithm for mining association rules
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public AlcalaetalProcess(myDataset dataset, int nEvaluations, int popSize, int nBitsGene, double phi, double d, int nFuzzyRegionsForNumericAttributes, boolean useMaxForOneFrequentItemsets, double minSupport, double minConfidence)
It creates a new process for the algorithm by setting up its parameters
dataset
- The instance of the dataset for dealing with its recordsnEvaluations
- The maximum number of evaluations to reach before stopping the genetic learningpopSize
- The maximum size of population to handle after each generationnBitsGene
- The number of bit digits for encoding a displacement within a genephi
- It represents the value used for decreasing the "L" threshold (CURRENTLY NOT USED)d
- It indicates the value for controlling the Parent Centric BLX crossovernFuzzyRegionsForNumericAttributes
- The number of fuzzy regions with which numeric attributes are evaluateduseMaxForOneFrequentItemsets
- It indicates whether the max operator must be used while discovering 1-Frequent ItemsetsminSupport
- The user-specified minimum support for the mined association rulesminConfidence
- The user-specified minimum confidence for the mined association rulespublic void run()
It runs the algorithm for mining association rules
public java.util.ArrayList<AssociationRule> getRulesSet()
It returns a rules set once the algorithm has been carried out
public void printReport(java.util.ArrayList<AssociationRule> rules)
It prints out on screen relevant information regarding the mined association rules
rules
- The array of association rules from which gathering relevant informationpublic int getNumberOfOneFrequentItemsets()
It returns the number of 1-Frequent Itemsets
public java.lang.String getGeneticLearningLog()
It returns the XML string representing the genetic learning log
public java.util.ArrayList<FuzzyAttribute> getUniformFuzzyAttributes()
It returns the uniform fuzzy attributes before running the genetic learning process
public java.util.ArrayList<FuzzyAttribute> getAdjustedFuzzyAttributes()
It returns the mined fuzzy attributes once the genetic learning has been accomplished