Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters

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Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters

K-means is an unsupervised learning and partitioning clustering algorithm. It is popular and widely used for its simplicity and fastness. K-means clustering produce a number of separate flat (non-hierarchical) clusters and suitable for generating globular clusters. The main drawback of the k-means...

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Bibliographic Details
Main Authors:	Wan Maseri, Wan Mohd, Beg, Abul Hashem, Herawan, Tutut, Noraziah, Ahmad
Format:	Article
Language:	English
Published:	IGI Global 2011
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/9328/ http://umpir.ump.edu.my/id/eprint/9328/7/improved-parameterless-k-means_-auto-generation-centroids-and-distance-data-point-clusters%281%29.pdf

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