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ROUGH SET: AN OVERVIEW

Rough Set Theory is a fairly new concept that has found applications to various soft computing techniques. It offers a set theory approach to manage the uncertainty in data systems. It has been used for the discovery of data dependencies, importance of features, patterns in sample data, feature space dimensionality reduction, and the classification of objects. Objects can be classified by means of their attributes when considered in the context of an approximation space. The Near Sets represent a generalization of Rough Sets. It presents a nearness approach to classifying objects. In this paper we present an overview of basics of rough sets and near sets along with their application to face recognition problem.