A Tolerance Rough Sets Theory-Based Knowledge Reduction Method in Knowledge Discovery in Databases

In order to overcome this shortage of general rough set theory, the elementary concept of tolerance rough set theory is proposed, and the theory is employed to build objects´ tolerance relations that can correctly classify objects in system. First, we use genetic algorithms to search for the optimal thresholds, then construct special matrix for attributes and objects. Thus we can get the relations among attributes and objects, and relative absorbent set of objects in detail. Furthermore, the method of using tolerance rough sets reduces the qualitative processing, improving the validness of knowledge reduction. Finally, we present examples illustrating our approaches in the paper.