A unified approach for cluster-wise and general noise rejection approaches for k-means clustering

A unified approach for cluster-wise and general noise rejection approaches for k-means clustering

Hard C-means (HCM; k-means) is one of the most widely used partitive clustering techniques. However, HCM is strongly affected by noise objects and cannot represent cluster overlap. To reduce the influence of noise objects, objects distant from cluster centers are rejected in some noise rejection app...

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Bibliographic Details
Main Author:	Seiki Ubukata
Format:	Article
Language:	English
Published:	PeerJ Inc. 2019-11-01
Series:	PeerJ Computer Science
Subjects:	Clustering k-means Noise rejection Rough set theory
Online Access:	https://peerj.com/articles/cs-238.pdf

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