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...
| Main Authors: | , , , |
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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/ http://umpir.ump.edu.my/id/eprint/9328/ 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 |