PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Gustafson-Kessel-like clustering algorithm based on typicality degrees
Marie-Jeanne Lesot and Rudolf Kruse
In: Int. Conf. on Information Processing and Management of Uncertainty, Paris, France(2006).


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 Gustafson- Kessel variant and makes it possible to identify ellipsoidal clusters with robustness as regards outliers.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:2927
Deposited By:Marie-Jeanne Lesot
Deposited On:23 November 2006