Selection of variables for cluster analysis and classification rules
统计理论
2023-12-29 v1 统计理论
摘要
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.
引用
@article{arxiv.math/0610757,
title = {Selection of variables for cluster analysis and classification rules},
author = {Ricardo Fraiman and Ana Justel and Marcela Svarc},
journal= {arXiv preprint arXiv:math/0610757},
year = {2023}
}
备注
28 pages, 7 figures