Two-phase clustering algorithm with density exploring distance measure

Here, the authors propose a novel two-phase clustering algorithm with a density exploring distance (DED) measure. In the first phase, the fast global K-means clustering algorithm is used to obtain the cluster number and the prototypes. Then, the prototypes of all these clusters and representatives o...

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Bibliographic Details
Main Authors:	Jingjing Ma, Xiangming Jiang, Maoguo Gong
Format:	Article
Language:	English
Published:	Wiley 2018-04-01
Series:	CAAI Transactions on Intelligence Technology
Subjects:	pattern clustering statistical distributions sorting DED measure data points UCI data sets comparison algorithms two-phase clustering algorithm cluster number density exploring distance measure fast global K-means clustering algorithm data distributions non-convex distribution
Online Access:	https://digital-library.theiet.org/content/journals/10.1049/trit.2018.0006

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https://digital-library.theiet.org/content/journals/10.1049/trit.2018.0006

Two-phase clustering algorithm with density exploring distance measure

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