What to Do When K-Means Clustering Fails: A Simple yet Principled Alternative Algorithm
The K-means algorithm is one of the most popular clustering algorithms in current use as it is relatively fast yet simple to understand and deploy in practice. Nevertheless, its use entails certain restrictive assumptions about the data, the negative consequences of which are not always immediately...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Public Library of Science
2017
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| Online Access: | http://hdl.handle.net/1721.1/109129 |