Design of Hierarchical Fuzzy Classification System Based on Statistical Characteristics of Data

被引：0
|
作者：
Son, Chang Sik [2 ]
Kim, Yoon-Nyun [3 ]
Park, Kyung-Ri
Park, Hee-Joon [1 ]
机构：
[1] Keimyung Univ, Sch Med, Dept Biomed Engn, Taegu, South Korea
[2] Keimyung Univ, Sch Med, Dept Med Informat, Taegu, South Korea
[3] Keimyung Univ, Sch Med, Dept Internal Med, Taegu, South Korea
来源：
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2010年 / E93D卷 / 08期
关键词：
hierarchical fuzzy classification system; fuzzy partitioning; rule generation; RULE EXTRACTION; APPROXIMATION;
D O I：
10.1587/transinf.E93.D.2319
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A scheme for designing a hierarchical fuzzy classification system with a different number of fuzzy partitions based on statistical characteristics of the data is proposed. To minimize the number of misclassified patterns in intermediate layers, a method of fuzzy partitioning from the defuzzified outputs of previous layers is also presented. The effectiveness of the proposed scheme is demonstrated by comparing the results from five datasets in the UCI Machine Learning Repository.
引用
收藏
页码：2319 / 2323
页数：5
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