A Fuzzy-Rough Approach for Case Base Maintenance

Abstract. This paper proposes a fuzzy-rough method of maintaining CaseBased Reasoning (CBR) systems. The methodology is mainly based on the idea that a large case library can be transformed to a small case library together with a group of adaptation rules, which take the form of fuzzy rulesgenerated bythe rough set technique. In paper [1], we have proposed a methodology for case base maintenance which used a fuzzy decision tree induction to discover the adaptation rules; in this paper, we focus on using a heuristic algorithm, i.e., a fuzzy-rough algorithm [2] in the process of simplifying fuzzy rules. This heuristic, regarded as a new fuzzy learning algorithm, has many significant advantages, such as rapid speed of training and matching, generating a family of fuzzy rules which is approximately simplest. By applying such a fuzzy-rough learning algorithm to the adaptation mining phase, the complexity of case base maintenance is reduced, and the adaptation knowledge is more compact and e...

• Type: Conference
• Year: 2001
• Where: ICCBR
• Authors: Guoqing Cao, Simon C. K. Shiu, Xizhao Wang
• Keywords: Adaptation Rules, Automated Reasoning, Case Base Maintenance, Fuzzy Rules, ICCBR 2001