FNM-based and RFCM-based Fuzzy Clustering for Tri-Relational Data

被引：0
|
作者：
Kanzawa, Yuchi [1 ]
机构：
[1] Shibaura Inst Technol, Tokyo 1358548, Japan
来源：
6TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS, AND THE 13TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS | 2012年
关键词：
C-MEANS; ALGORITHMS;
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：
In this paper, some fuzzy clustering methods are proposed for relational data which represents the dissimilarity for triples of data points. One method is based on the fuzzy nonmetric model and the other is on the relational fuzzy c-means. Each method has two options of fuzzification; the standard and the entropy-regularization. Through some numerical experiments, the feature of the proposed methods is discussed.
引用
收藏
页码：1982 / 1987
页数：6
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