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Knowledge discovery using a new interpretable simulated annealing based fuzzy classification system

Mohamadia, H ; Sharif University of Technology | 2009

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  1. Type of Document: Article
  2. DOI: 10.1109/ACIIDS.2009.63
  3. Publisher: 2009
  4. Abstract:
  5. This paper presents a new interpretable fuzzy classification system. Simulated annealing heuristic is employed to effectively investigate the large search space usually associated with classification problem. Here, two criteria are used to evaluate the proposed method. The first criterion is accuracy of extracted fuzzy if-then rules, and the other is comprehensibility of obtained rules. Experiments are performed with some data sets from UCI machine learning repository. Results are compared with several well-known classification algorithms, and show that the proposed approach provides more accurate and interpretable classification system. © 2009 IEEE
  6. Keywords:
  7. Classification algorithm ; Classification system ; Data sets ; Fuzzy classification systems ; Fuzzy if-then rules ; Knowledge Discovery ; Search spaces ; UCI machine learning repository ; Database systems ; Fuzzy systems ; Simulated annealing
  8. Source: Proceedings - 2009 1st Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009, 1 April 2009 through 3 April 2009, Dong Hoi ; 2009 , Pages 271-276 ; 9780769535807 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/5176005