Decision rule merging method considering the number of acquisition rules

Abstract

Rough set theory was proposed by Z.Pawlak in 1982. This theory can mine knowledge through a decision rule from a database, a web base, a set and so on. The decision rule is used for data analysis as well. And we can reason for an unknown object using the decision rule. However, there are cases where too many decision rules are found. It is difficult to acquire knowledge from too many rules. However, the C.I. value of the merged decision rule may be low. In addition, if the obtained minimum determination rules are merged by reducing the number of conditional attributes, the number of rules may increase.In this paper, we investigate how to set the optimum number of conditional attributes and the number of conditional attribute categories. We consider appropriate decision rule merging methods for use in knowledge acquisition.