Attribute reduction of decision table based on similar relation

In this paper, we study attribute reduction of decision system based on similar relations. We first define the concept of attribute reduction. We then develop a sufficient and necessary condition for attribute reduction and construct the dicernibility matrix on similar relations, by which we can compute all the reducts of decision systems. The experimental results with UCI data sets show that the proposed reduction approach is an effective method to deal with numerical and categorical data sets.