Discovering fuzzy association rules using fuzzy partition methods

被引：55

作者：

Hu, YC

Chen, RS

Tzeng, GH ^{[1
]}

机构：

[1] Natl Chiao Tung Univ, Inst Management & Technol, Hsinchu 300, Taiwan

[2] Natl Tsing Hua Univ, Inst Management & Technol, Hsinchu 300, Taiwan

来源：

KNOWLEDGE-BASED SYSTEMS | 2003年 / 16卷 / 03期

关键词：

data mining; fuzzy partition; association rules; decision making;

D O I：

10.1016/S0950-7051(02)00079-5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Fuzzy association rules described by the natural language are well suited for the thinking of human subjects and will help to increase the flexibility for supporting users in making decisions or designing the fuzzy systems. In this paper, a new algorithm named fuzzy grids based rules mining algorithm (FGBRMA) is proposed to generate fuzzy association rules from a relational database. The proposed algorithm consists of two phases: one to generate the large fuzzy grids, and the other to generate the fuzzy association rules. A numerical example is presented to illustrate a detailed process for finding the fuzzy association rules from a specified database, demonstrating the effectiveness of the proposed algorithm. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：137 / 147

页数：11

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