⾼次元⼩標本データに対するT-ノルムに基づくマルチレイヤークラスタリング

伊藤 佳輝; 元田 卓; 佐藤 美佳

doi:10.14864/fss.34.0_480

34th Fuzzy System Symposium

Session ID : TC2-1

DOI https://doi.org/10.14864/fss.34.0_480

Conference information

Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)

Name : 34th Fuzzy System Symposium

Number : 34

Location : [in Japanese]

Date : September 03, 2018 - September 05, 2018

proceeding

Multilayer Clustering based on T-norms for High-Dimension Low-Sample Size Data

*Yoshiki ITO, Suguru MOTODA, Mika SATO-ILIC

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Keywords: Multilayer Clustering, T-norm, High-Dimension Low-Sample Size Data

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Abstract

In this paper, multilayer clustering based on T-norms for high-dimension low-sample size (HDLSS) data is proposed. In order to reduce the number of variables of HDLSS data, a variable selection method based on fuzzy clustering is employed. Numerical examples show better performance of the proposed method.

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