Class AlgoTRuleGrowth
- java.lang.Object
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- org.processmining.logfiltering.algorithms.SPMF.AlgoTRuleGrowth
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public class AlgoTRuleGrowth extends java.lang.ObjectThis is the original implementation of the TRULEGROWTH algorithm for mining sequential rules with a window size constraint. The TRuleGrowth algorithm is a variation of the RuleGrowth algorithm described in this paper:
Fournier-Viger, P., Wu, C.-W., Tseng, V.S., Nkambou, R. (2012). Mining Sequential Rules Common to Several Sequences with the Window Size Constraint. Proceedings of the 25th Canadian Conf. on Artificial Intelligence (AI 2012), Springer, LNAI 7310, pp.299-304.- Author:
- Philippe Fournier-Viger
- See Also:
Sequence,SequenceDatabase
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Constructor Summary
Constructors Constructor Description AlgoTRuleGrowth()Default constructor
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description doublegetTotalTime()Get the total runtime of the last execution.java.lang.String[]inputRules()java.lang.String[]outputRules()voidprintStats()Print statistics about the last algorithm execution to System.out.voidrunAlgorithm(double minSupport, double minConfidence, java.lang.String input, java.lang.String output, int windowSize)Run the algorithm.voidrunAlgorithm(java.lang.String input, java.lang.String output, int relativeMinSupport, double minConfidence, int windowSize)Run the algorithm.voidsetMaxAntecedentSize(int maxAntecedentSize)Set the number of items that a rule antecedent should contain (optional).voidsetMaxConsequentSize(int maxConsequentSize)Set the number of items that a rule consequent should contain (optional).
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Method Detail
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runAlgorithm
public void runAlgorithm(double minSupport, double minConfidence, java.lang.String input, java.lang.String output, int windowSize) throws java.io.IOExceptionRun the algorithm.- Parameters:
minSupport- Minsup as a percentage (ex: 0.05 = 5 %)minConfidence- minimum confidence (a value between 0 and 1).input- the input file pathoutput- the output file pathwindowSize- a window size- Throws:
java.io.IOException- exception if there is an error reading/writing files
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runAlgorithm
public void runAlgorithm(java.lang.String input, java.lang.String output, int relativeMinSupport, double minConfidence, int windowSize) throws java.io.IOExceptionRun the algorithm.- Parameters:
relativeMinSupport- the minsup parameter as a a relative value (integer)minConfidence- minimum confidence (a value between 0 and 1).input- the input file pathoutput- the output file pathwindowSize- a window size- Throws:
java.io.IOException- exception if there is an error reading/writing files
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inputRules
public java.lang.String[] inputRules()
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outputRules
public java.lang.String[] outputRules()
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setMaxAntecedentSize
public void setMaxAntecedentSize(int maxAntecedentSize)
Set the number of items that a rule antecedent should contain (optional).- Parameters:
maxAntecedentSize- the maximum number of items
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setMaxConsequentSize
public void setMaxConsequentSize(int maxConsequentSize)
Set the number of items that a rule consequent should contain (optional).- Parameters:
maxConsequentSize- the maximum number of items
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printStats
public void printStats()
Print statistics about the last algorithm execution to System.out.
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getTotalTime
public double getTotalTime()
Get the total runtime of the last execution.- Returns:
- the time as a double.
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