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Gustafson-Kessel-like clustering algorithm based on typicality degrees
| Content Provider | Semantic Scholar |
|---|---|
| Author | Lesot, Marie-Jeanne |
| Copyright Year | 2006 |
| Abstract | Typicality degrees were defined in supervised learning as a tool to build characteristic representatives for data categories. In this paper, an extension of these typicality degrees to unsupervised learning is proposed to perform clustering. The proposed algorithm constitutes a GustafsonKessel variant and makes it possible to identify ellipsoidal clusters with robustness as regards outliers. |
| File Format | PDF HTM / HTML |
| DOI | 10.1142/9789812792358_0009 |
| Alternate Webpage(s) | http://www-apa.lip6.fr/~lesot/LesotKruseIPMU06/ |
| Alternate Webpage(s) | http://webia.lip6.fr/~lesot/LesotKruseIPMU06 |
| Alternate Webpage(s) | http://www.math.s.chiba-u.ac.jp/~yasuda/open2all/Paris06/IPMU2006/HTML/FINALPAPERS/P160.PDF |
| Alternate Webpage(s) | https://doi.org/10.1142/9789812792358_0009 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |