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A Fuzzy Validity-Guided Procedure for Cluster Detection

Benrabh, Mohamed and Bouroumi, Abdelaziz and Hamdoun, Abdellatif (2005) A Fuzzy Validity-Guided Procedure for Cluster Detection. Malaysian Journal of Computer Science, 18 (1). pp. 31-39. ISSN 0127-9084

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Official URL: http://mjcs.fsktm.um.edu.my/detail.asp?AID=321

Affiliations

Université Hassan II-Mohammedia

Abstract

In this paper, we present a new procedure for detecting clusters within unlabelled data sets of the form X = {x1, x2,…,xn}? Rp. This procedure quickly explores the elements of X with the main goal of discovering the clusters they form. It provides, in addition to the number of clusters, an initial prototype of each detected cluster. For this, the only assumptions made are that (1) the two least similar elements of belong necessarily to two different clusters, and (2) each element possesses a level of similarity with its nearest prototype greater than a certain threshold. This threshold can be either user defined or automatically determined by the algorithm using a validation process. The effectiveness of this method is demonstrated on both synthetic and real test data sets.

Item Type:Journal
Keywords:Unsupervised learning, Fuzzy clustering, Cluster validity, Pattern recognition
Subjects:Q Science
ID Code:382

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