SURVEY OF METHODS FOR EXTRACTING FUZZY RULES USING CLASSIFICATION AMBIGUITY

被引：0

作者：

Bohacik, Jan ^{[1
]}

机构：

[1] Univ Zilina, Fac Management Sci & Informat, Dept Informat, Zilina, Slovakia

来源：

INTERNATIONAL JOURNAL ON INFORMATION TECHNOLOGIES AND SECURITY | 2010年 / 2卷 / 02期

关键词：

fuzzy rules; classification ambiguity; transportation systems;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

For effectiveness and user-friendliness of fuzzy rules, their extraction is becoming more-and-more popular technique in Data Mining. In this paper, two methods for extracting fuzzy rules using classification ambiguity are analyzed and summarized in a united terminology using notions of fuzzy logic. They are experimentally compared on the basis of their error rates on testing databases from the UCI ML Repository. It seems elimination of linguistic variables allows to achieve lower average error rates than reduction of classification ambiguity.

引用

页码：33 / 44

页数：12

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