Extraction of Fuzzy Rules from Data using Rough Set

Rough Set을 이용한 퍼지 규칙의 생성

Rough Set theory suggested by Pawlak has a property that it can describe the degree of relation between condition and decision attributes of data which don't have linguistic information. In this paper, by using this ability of rough set theory, we define a occupancy degree which is a measure can represent a degree of relational quantity between condition and decision attributes of data table. We also propose a method that can find an optimal fuzzy rule table and membership functions of input and output variables from data without linguistic information and examine the validity of the method by modeling data generated by fuzzy rule.