Gustafson-Kessel-like clustering algorithm based on typicality degrees
نویسندگان
چکیده
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.
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