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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Main Authors: | Wan Maseri, Wan Mohd, Beg, Abul Hashem, Herawan, Tutut, Noraziah, Ahmad |
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Format: | Article |
Language: | English |
Published: |
IGI Global
2011
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Subjects: | |
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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