A selection method of interrelated attributes based on representation ability in interrelationship mining

Abstract

Rough-set-based interrelationship mining is a framework for mining characteristics between two different attributes using attributes called interrelated attributes. Interrelated attributes represent comparison of values of two different attributes, and adding these to data, it is capable to extract characteristics between attributes within a framework of rough-set-based data analysis. However, when there are numerous interrelated attributes we can consider, if adding all of them, then it requires a lot of computation time. Therefore, we propose a selection method of interrelated attributes based on representation ability.