Analysis of Measures of Quantitative Association Rules

Description

This paper presents the analysis of relationships among different interestingness measures of quality of association rules as first step to select the best objectives in order to develop a multi-objective algorithm. For this purpose, the discovering of association rules is based on evolutionary techniques. Specifically, a genetic algorithm has been used in order to mine quantitative association rules and determine the intervals on the attributes without discretizing the data before. The algorithm has been applied in real-word climatological datasets based on Ozone and Earthquake data.

Abstract

Ministerio de Ciencia y Tecnología TIN2007-68084-C-00

Abstract

Junta de Andalucía P07-TIC-02611

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