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A method of identifying influential data in fuzzy clustering

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Title: A method of identifying influential data in fuzzy clustering
Authors: Imai, Hideyuki1 Browse this author →KAKEN DB
Tanaka, Akira Browse this author →KAKEN DB
Miyakoshi, Masaaki Browse this author
Authors(alt): 今井, 英幸1
Issue Date: Feb-1998
Publisher: IEEE
Journal Title: IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume: 6
Issue: 1
Start Page: 90
End Page: 101
Publisher DOI: 10.1109/91.660810
Abstract: In multivariate statistical methods, it is important to identify influential observations for a reasonable interpretation of the data structure. In this paper, we propose a method for identifying influential data in the fuzzy C-means (FCM) algorithm. To investigate such data, we consider a perturbation of the data points and evaluate the effect of a perturbation. As a perturbation, we consider two cases: one is the case in which the direction of a perturbation is specified and the other is the case in which the direction of a perturbation is not specified. By computing the change in the clustering result of FCM when given data points are slightly perturbed, we can look for data points that greatly affect the result. Also, we confirm an efficacy of the proposed method by numerical examples.
Rights: © 1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” IEEE, IEEE TRANSACTIONS ON FUZZY SYSTEMS, Volume 6, Issue 1, 1998 Page(s):90 - 101
Type: article
URI: http://hdl.handle.net/2115/5843
Appears in Collections:情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 今井 英幸

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