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» Extreme logistic regression
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SCFBM
2008
738views more  SCFBM 2008»
14 years 9 months ago
Purposeful selection of variables in logistic regression
The main problem in any model-building situation is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a vari...
Zoran Bursac, C. Heath Gauss, David Keith Williams...
BMCBI
2008
127views more  BMCBI 2008»
14 years 9 months ago
Gene and pathway identification with Lp penalized Bayesian logistic regression
Background: Identifying genes and pathways associated with diseases such as cancer has been a subject of considerable research in recent years in the area of bioinformatics and co...
Zhenqiu Liu, Ronald B. Gartenhaus, Ming Tan, Feng ...
ICML
2004
IEEE
15 years 10 months ago
Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
ICML
2005
IEEE
15 years 10 months ago
Logistic regression with an auxiliary data source
Xuejun Liao, Ya Xue, Lawrence Carin
KDD
2008
ACM
111views Data Mining» more  KDD 2008»
15 years 10 months ago
Fast logistic regression for text categorization with variable-length n-grams
Gökhan H. Bakir, Georgiana Ifrim, Gerhard Wei...