Robust-learning fuzzy c-means clustering algorithm with unknown number of clusters

•We construct a robust learning-based fuzzy c-means (FCM) framework, called the robust-learning FCM (RL-FCM) algorithm.•The proposed RL-FCM can automatically find the best number of clusters, without any initialization and parameter selection with free of the fuzziness index m.•The computational com...

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Bibliographic Details

Published in:	Pattern recognition Vol. 71; pp. 45 - 59
Main Authors:	Yang, Miin-Shen, Nataliani, Yessica
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2017
Subjects:	Entropy penalty terms Fuzzy c-means (FCM) Fuzzy clustering Number of clusters Robust learning-based schema Robust-learning FCM (RL-FCM) Robust learning-based schema Fuzzy clustering Number of clusters Fuzzy c-means (FCM) Robust-learning FCM (RL-FCM) Entropy penalty terms
ISSN:	0031-3203, 1873-5142
Online Access:	Get full text
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