open access

https://hdl.handle.net/2115/5843

A method of identifying influential data in fuzzy clustering

英語

1998-02

IEEE

IEEE TRANSACTIONS ON FUZZY SYSTEMS

6(1)

90-101

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.

学術雑誌論文

Version of Record

© 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

1063-6706