Sciweavers

Share
PRL
2006

Feature selection in robust clustering based on Laplace mixture

8 years 11 months ago
Feature selection in robust clustering based on Laplace mixture
A wrapped feature selection process is proposed in the context of robust clustering based on Laplace mixture models. The clustering approach we consider is a generalization of the K-median algorithm. The selection process makes use of the statistical model and recursively deletes features using hypothesis tests. We report simulations and applications to real data sets which illustrate the relevance of the proposed approach. We propose a strategy to select a reasonable number of remaining features. It uses the test statistic to choose the most relevant features, then an evaluation of the clustering error to discard the redundant ones from among them. This strategy appears to produce a good compromise between the selection of features and the performance of the clustering.
Aurélien Cord, Christophe Ambroise, Jean Pi
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where PRL
Authors Aurélien Cord, Christophe Ambroise, Jean Pierre Cocquerez
Comments (0)
books