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A Sparse Version of the Ridge Logistic Regression for Large-Scale Text Categorization
 

Summary: A Sparse Version of the Ridge Logistic Regression for
Large-Scale Text Categorization
Sujeevan Aseervathama,
, Anestis Antoniadisb
, Eric Gaussiera
, Michel Burletc
,
Yves Denneulind
a LIG - Universit´e Joseph Fourier, 385, rue de la Biblioth`eque, BP 53, F-38041 Grenoble
Cedex 9, France
b LJK - Universit´e Joseph Fourier, BP 53, F-38041 Grenoble Cedex 9, France
c Lab. Leibniz - Universit´e Joseph Fourier, 46 Avenue F´elix Viallet, F-38031 Grenoble
Cedex 1, France
d LIG - ENSIMAG, 51 avenue Jean Kuntzmann, F-38330 Montbonnot Saint Martin,
France
Abstract
The ridge logistic regression has successfully been used in text categorization
problems and it has been shown to reach the same performance as the Support
Vector Machine but with the main advantage of computing a probability value
rather than a score. However, the dense solution of the ridge makes its use un-

  

Source: Antoniadis, Anestis - Laboratoire Jean Kuntzmann, Université Joseph Fourier

 

Collections: Mathematics