Attribute Reduction and Rule Acquisition of Formal Decision Context Based on Dual Concept Lattice

Abstract

Concept lattice theory is a powerful tool for analyzing and extracting information from data sets. Rule acquisition and attribute reduction are hot research topics in formal concept analysis. This paper mainly proposes three kinds of rules based on formal concepts and dual concepts. In addition, the methods of rule acquisition for different kinds of rules are presented. Finally, the attribute reduction approaches to preserve different kinds of rules are given by using discernibility matrix.