A unified approach for cluster-wise and general noise rejection approaches for k-means clustering
Hard C-means (HCM; k-means) is one of the most widely used partitive clustering techniques. However, HCM is strongly affected by noise objects and cannot represent cluster overlap. To reduce the influence of noise objects, objects distant from cluster centers are rejected in some noise rejection app...
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2019-11-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-238.pdf |