Selection of variables for cluster analysis and classification rules

Details Selection of variables for cluster analysis and classification rules Selection of variables for cluster analysis and classification rules

2006-10-25

arxiv.org/abs/math/0610757v1

Mathematics

Statistics Theory

28 pages, 7 figures

Scientific paper

In this paper we introduce two procedures for variable selection in cluster analysis and classification rules. One is mainly oriented to detect the noisy non-informative variables, while the other deals also with multicolinearity. A forward-backward algorithm is also proposed to make feasible these procedures in large data sets. A small simulation is performed and some real data examples are analyzed.

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