Self-Adaptive Multiprototype-Based Competitive Learning Approach: A k-Means-Type Algorithm for Imbalanced Data Clustering

Class imbalance problem has been extensively studied in the recent years, but imbalanced data clustering in unsupervised environment, that is, the number of samples among clusters is imbalanced, has yet to be well studied. This paper, therefore, studies the imbalanced data clustering problem within...

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Bibliographic Details
Published in:	IEEE transactions on cybernetics Vol. 51; no. 3; pp. 1598 - 1612
Main Authors:	Lu, Yang, Cheung, Yiu-Ming, Tang, Yuan Yan
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.03.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">k -means-type algorithm Algorithms Class imbalance learning Clustering Clustering algorithms Competition competitive learning Cybernetics data clustering Density measurement internal validation measure Learning systems Machine learning Merging multiprototype clustering Power capacitors Prototypes
ISSN:	2168-2267, 2168-2275, 2168-2275
Online Access:	Get full text
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