Evaluation of Fuzzy Clustering for High-Dimensional Data based on Principal Component Analysis
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- Murayama Takanori
- University of Tuskuba
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- Sato-Ilic Mika
- University of Tuskuba
Bibliographic Information
- Other Title
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- 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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Abstract
<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
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- Proceedings of the Fuzzy System Symposium
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Proceedings of the Fuzzy System Symposium 35 (0), 203-208, 2019
Japan Society for Fuzzy Theory and Intelligent Informatics
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Details 詳細情報について
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- CRID
- 1390846609786346880
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- NII Article ID
- 130007772942
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- NII Book ID
- AA12165648
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- ISSN
- 18820212
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- NDL BIB ID
- 029975932
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed