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http://dx.doi.org/10.5351/CSAM.2014.21.1.061

Logistic Regression Classification by Principal Component Selection  

Kim, Kiho (Department of Statistics, Hankuk University of Foreign Studies)
Lee, Seokho (Department of Statistics, Hankuk University of Foreign Studies)
Publication Information
Communications for Statistical Applications and Methods / v.21, no.1, 2014 , pp. 61-68 More about this Journal
Abstract
We propose binary classification methods by modifying logistic regression classification. We use variable selection procedures instead of original variables to select the principal components. We describe the resulting classifiers and discuss their properties. The performance of our proposals are illustrated numerically and compared with other existing classification methods using synthetic and real datasets.
Keywords
Logistic regression classification; principal components; sparse regression;
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