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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Vydáno v:	IEEE transactions on cybernetics Ročník 51; číslo 3; s. 1598 - 1612
Hlavní autoři:	Lu, Yang, Cheung, Yiu-Ming, Tang, Yuan Yan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.03.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	<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
On-line přístup:	Získat plný text
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