A New Measure For Clustering Model Selection
A new method for determining the number of k-means clusters in a given data set is presented. The algorithm is developed from a theoretical perspective and then its implementation is examined and compared to existing solutions.
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| Language: | en |
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2008
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| Online Access: | http://hdl.handle.net/10012/3697 |