Proposal of Notation of Rough Set Theory Based Decision Rule Condition Part Applying Formal Concept Analysis Based Inclusion Relation

Abstract

In recent years, rough set theory has attracted attention as one of the data mining techniques. However, when there are tens or hundreds of decision rules extracted as a result of analysis, it is difficult to identify the combination of attribute values with high frequency of occurrence (core) and the inclusion relations among decision rules and attribute values. Therefore, the purpose of this study was to develop a notation that reflects the extraction of cores in decision rules and the inclusion relations between attributes obtained by formal concept analysis in the decision rule condition part. This enabled us to discover inclusion relations between decision rules and affinity between cores and attribute values, which were difficult to discover in rough set theory alone. We also verified the usefulness of the proposed notation by comparing the proposed notation with the conventional decision rule notation using two example problems as case studies.