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| Title: | Impact of contamination on training and test error rates in
statistical clustering |
| Authors: | Ruwet, Christel
Haesbroeck, Gentiane |
| Issue Date: | 4-Feb-2011 |
| Publisher: | Taylor & Francis |
| Abstract: | Abstract
The k-means algorithm is one of the most common nonhierarchical clustering methods. However, this procedure is not robust with respect to atypical observations. Alternative techniques have thus been introduced, e.g. the generalized k-means procedure. In this paper, focus is on the error rate these procedures achieve when one expects the data to be distributed according to a mixture distribution. Two different definitions of the error rate are under consideration, depending on the data at hand. |
| URI: | http://repository.peerproject.eu:8080/jspui/handle/123456789/19461 |
| ISSN: | 0361-0918 (pISSN)
1532-4141 (eISSN) |
| Appears in Collections: | PEER articles
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