Ensembles of Classifiers Based on Approximate Reducts

Issue title: Concurrency Specification and Programming (CS&P'2000)

Article type: Research Article

Authors: Wróblewski, Jakub^;

Affiliations: Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warsaw, Poland | Institute of Mathematics, Warsaw University, ul. Banacha 2, 02-097 Warsaw, Poland

Abstract: The problem of improving rough set based expert systems by modifying a notion of reduct is discussed. The notion of approximate reduct is introduced, as well as some proposals of quality measure for such a reduct. The complete classifying system based on approximate reducts is presented and discussed. It is proved that the problem of finding optimal set of classifying agents based on approximate reducts is NP-hard; the genetic algorithm is applied to find the suboptimal set. Experimental results show that the classifying system is effective and relatively fast.

Keywords: Rough sets, approximate reduct, voting

Journal: Fundamenta Informaticae, vol. 47, no. 3-4, pp. 351-360, 2001