Fuzzy rules generation method for classification problems using rough sets and genetic algorithms

被引：0
|
作者：
Sikora, M [1 ]
机构：
[1] Silesian Tech Univ, Inst Comp Sci, PL-44100 Gliwice, Poland
来源：
ROUGH SETS, FUZZY SETS, DATA MINING, AND GRANULAR COMPUTING, PRT 1, PROCEEDINGS | 2005年 / 3641卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A method of constructing a classifier that uses fuzzy reasoning is described in this paper. Rules for this classifier are obtained by means of algorithms relying on a tolerance rough sets model. Got rules are in so called sharp" form, a genetic algorithm is used for fuzzification of these rules. Presented results of experiments show that the proposed method allows getting a smaller rules set with similar (or better) classification abilities.
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页码：383 / 391
页数：9
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