ROUGH SETS REDUCTION FOR BINARY DATA

Document Type : Original Article

Authors

1 Department of Engineering Mathmatics & Basic Science, Facully of Engineering, Minoufva University, Shebin El-Kom, Egypt

2 Department of Engineering Mathmatics & Basic Science, Faculty of Engineering, Tanta University, Egypt

3 *Institute of Statistical Studies & Research (ISSR), Cairo Universify, Egyp

Abstract

The major aim of this work is to introduce a new method for data reduction in information systems
classified by nonequivalence relations. The suggested approach is useful for many real life data
that can not be classsed into disjoint classes. The new approach is tested with examples and its
ability for decreasing the noisy in data, as well as simpliiing the structure for extracting decision
rules. Based on binary relation, this method is capable of discovering the reduct attributes or
indispensable attributes which are useful for data description andlor prediction, and to remove the
dispensable ones.

Keywords