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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/9328/7/improved-parameterless-k-means_-auto-generation-centroids-and-distance-data-point-clusters%281%29.pdf
http://umpir.ump.edu.my/id/eprint/9328/
http://www.igi-global.com/article/improved-parameterless-means/64168
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http://umpir.ump.edu.my/id/eprint/9328/7/improved-parameterless-k-means_-auto-generation-centroids-and-distance-data-point-clusters%281%29.pdf
http://umpir.ump.edu.my/id/eprint/9328/
http://www.igi-global.com/article/improved-parameterless-means/64168

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