On Fuzzy Clustering for Incomplete Spherical Data and for Incomplete Multivariate Categorical Data

被引：0

作者：

Kanzawa, Yuchi ^{[1
]}

机构：

[1] Shibaura Inst Technol, Tokyo, Japan

来源：

2018 JOINT 10TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 19TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS) | 2018年

关键词：

Incomplete Spherical Data; Incomplete Categorical Multivariate Data; Fuzzy Clustering; Optimal Completion Strategy;

D O I：

10.1109/SCIS-ISIS.2018.00107

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, six fuzzy clustering algorithms for incomplete data are proposed that use the optimal completion strategy, three of which are for incomplete spherical data and these of which are for incomplete categorical multivariate data. In numerical experiments using a real dataset, each of the proposed methods outperformed its counterpart method based on the whole data strategy (WDS) in terms of accuracy.

引用

页码：638 / 643

页数：6

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