ca.pfv.spmf.algorithms.associationrules.TopKRules_and_TNR

Class AlgoTopKRules

java.lang.Object

ca.pfv.spmf.algorithms.associationrules.TopKRules_and_TNR.AlgoTopKRules

public class AlgoTopKRules
extends java.lang.Object

TopKRules is an algorithm for mining the TOP-K association rules from a transaction database using a pattern growth approach and several optimizations. This is the original implementation as proposed in the following paper:

Fournier-Viger, P., Wu, C.-W., Tseng, V. S. (2012). Mining Top-K Association Rules. Proceedings of the 25th Canadian Conf. on Artificial Intelligence (AI 2012), Springer, LNAI 7310, pp. 61-73.

Constructor Summary

Constructors

Constructor and Description
AlgoTopKRules() Default constructor

Method Summary

Modifier and Type	Method and Description
void	printStats() Print statistics about the last algorithm execution.
void	runAlgorithm(int k, double minConfidence, Database database) Run the algorithm.
void	writeResultTofile(java.lang.String path) Write the rules found to an output file.

Methods inherited from class java.lang.Object

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

Constructor Detail

AlgoTopKRules

public AlgoTopKRules()

Default constructor

Method Detail

runAlgorithm

public void runAlgorithm(int k,
                         double minConfidence,
                         Database database)

Run the algorithm.

Parameters:

k - the value of k.

minConfidence - the minimum confidence threshold.

database - the database.

printStats

public void printStats()

Print statistics about the last algorithm execution.

writeResultTofile

public void writeResultTofile(java.lang.String path)
                       throws java.io.IOException

Write the rules found to an output file.

Parameters:

path - the path to the output file

Throws:

java.io.IOException - exception if an error while writing the file