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Logistic Regression Classification by Principal Component Selection
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 Title & Authors
Logistic Regression Classification by Principal Component Selection
Kim, Kiho; Lee, Seokho;
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 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;
 Language
English
 Cited by
1.
Principal Component Regression by Principal Component Selection,;;;

Communications for Statistical Applications and Methods, 2015. vol.22. 2, pp.173-180 crossref(new window)
1.
Principal Component Regression by Principal Component Selection, Communications for Statistical Applications and Methods, 2015, 22, 2, 173  crossref(new windwow)
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