A New Fuzzy Rule Generation Scheme based on Multiple-Selection of Influencing Factors

MUTLU BİLGE B., SEZER E.

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Louisiana, United States Of America, 23 - 26 June 2019 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/fuzz-ieee.2019.8858990
  • City: Louisiana
  • Country: United States Of America
  • Hacettepe University Affiliated: Yes

Abstract

Automatic rule generation of fuzzy systems is a extensively studied topic which is generally handled by using a labeled dataset. This paper presents a new method for this problem which does not rely on training data. It only requests a tiny information which can be roughly acquired from any data and/or domain expert. By using this information, it selects single or multiple influencing factor(s) to determine the consequent part of rules. The experiments were performed on software fault prediction problem, and the resulting rules are compared with the rules obtained from 3 existing rule generation methods which are data-based, expert-based and partially data-based solutions. Results shows that, the proposed method is able to outperform its counterparts in most of the cases.