Evaluation of Fuzzy Clustering for High-Dimensional Data based on Principal Component Analysis

Murayama Takanori, Sato-Ilic Mika

doi:10.14864/fss.35.0_203

Bibliographic Information

Other Title

高次元データに対するファジィクラスタリングの主成分分析による評価
コウジゲンデータニタイスルファジィクラスタリングノシュセイブンブンセキニヨルヒョウカ

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Description

<p>This paper presents numerical results of the evaluation of fuzzy clustering results by using the technique of principal component analysis. In this case, we evaluate the eﬃciency of the fuzzy clustering results by utilizing probabilistic fuzzy clustering, possibilistic fuzzy clustering, and covariance based fuzzy clustering.</p>

Journal

Proceedings of the Fuzzy System Symposium

Proceedings of the Fuzzy System Symposium 35 (0), 203-208, 2019

Japan Society for Fuzzy Theory and Intelligent Informatics

Details 詳細情報について

CRID: 1390846609786346880

NII Article ID: 130007772942

NII Book ID: AA12165648

ISSN: 18820212

DOI: 10.14864/fss.35.0_203

NDL BIB ID: 029975932

Web Site: http://id.ndl.go.jp/bib/029975932; https://ndlsearch.ndl.go.jp/books/R000000004-I029975932

Text Lang: ja

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