Ensembles of Classifiers Based on Approximate Reducts
Jakub Wróblewski · 2001
. A problem of improving rough set based expert systems by modifying a notion of reduct is discussed. A notion of approximate reduct is introduced, as well as some proposals of quality measure for such a reduct. A complete classifying system based on approximate reducts is presented and discussed. It is proved that a problem of nding optimal set of classifying agents based on approximate reducts is NP-hard; a genetic algorithm is used to nd the suboptimal set. Experimental results show, that the classifying system is eective and relatively fast. 1 Introduction Rough set expert systems base on the notion of reduct [11], [12], a minimal subset of attributes which is sucient to discern between objects with dierent decision values. A set of short reducts can be used to generate rules [2]. A problem of short reducts generation is NP-hard, but an approximate algorithm (like the genetic one described in [13], [8] and implemented successfully { see [10]) can be used to obtain redu...