Абстрактный

FEATURE SELECTION BY ROUGH ��?QUICK REDUCT ALGORITHM

K.Anitha , Dr.P.Venkatesan

Feature Selection the process of finding the optimal subset for a given supplied data. In this paper we discuss about basic concepts and applications of Rough Set Theory in Feature Selection. The main advantage of Rough Set Feature Selection is it requires no additional parameters other than the original data. Rough Set is especially useful for domains where data collected are imprecise or incomplete about the domain objects. In this paper Quick-Reduct Algorithm is used to reduce the number of genes from gene expression data.