public class MOPNARProcess
extends java.lang.Object
Constructor and Description |
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MOPNARProcess(myDataset dataset,
int numObjectives,
int nTrials,
int H,
int T,
double probDelta,
int nr,
double pm,
double af,
double percentUpdate)
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<AssociationRule> |
generateRulesPareto() |
java.lang.String |
getParetos() |
void |
printPareto() |
void |
removeRedundant(java.util.ArrayList<Chromosome> upop) |
void |
run()
It runs the evolutionary learning for mining association rules
|
void |
saveReport(java.util.ArrayList<AssociationRule> rules,
java.io.PrintWriter w) |
public MOPNARProcess(myDataset dataset, int numObjectives, int nTrials, int H, int T, double probDelta, int nr, double pm, double af, double percentUpdate)
It creates a new process for the algorithm by setting up its parameters
dataset
- The instance of the dataset for dealing with its recordsnumObjectives
- The number of objectives to be optimizednTrials
- The maximum number of generations to reach before completing the whole evolutionary learningH
- The parameter to control the population size and weight vectorsT
- The number of the weight vectors in the neighborhoodprobDelta
- The probability that parent solutions are selected from the neighborhoodnr
- The maximal number of solutions replaced by each child solutionpm
- The probability for the mutation operatoraf
- The factor of amplitude for each attribute of the datasetpercentUpdate
- The difference threshold to restart the populationpublic void run()
It runs the evolutionary learning for mining association rules
public void saveReport(java.util.ArrayList<AssociationRule> rules, java.io.PrintWriter w)
public void removeRedundant(java.util.ArrayList<Chromosome> upop)
public void printPareto()
public java.util.ArrayList<AssociationRule> generateRulesPareto()
public java.lang.String getParetos()