Influence of fuzzy norms and other heuristics on "Mixed fuzzy rule formation"

被引:22
|
作者
Gabriel, TR
Berthold, MR
机构
[1] Univ Konstanz, Dept Comp & Informat Sci, D-78457 Constance, Germany
[2] Tripos Inc, Data Anal Res Lab, San Francisco, CA 94080 USA
关键词
D O I
10.1016/j.ijar.2003.10.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In Mixed Fuzzy Rule Formation [Int. J. Approx. Reason. 32 (2003) 67] a method to extract mixed fuzzy rules from data was introduced. The underlying algorithm's performance is influenced by the choice of fuzzy t-norm and t-conorm, and a heuristic to avoid conflicts between patterns and rules of different classes throughout training. In the following addendum to [Int. J. Approx. Reason. 32 (2003) 67], we discuss in more depth how these parameters affect the generalization performance of the resulting fuzzy rule models. (C) 2003 Elsevier Inc. All rights reserved.
引用
收藏
页码:195 / 202
页数:8
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