Efficient model selection for kernel logistic regression

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. ◽

10.1109/icpr.2004.1334249 ◽

2004 ◽

Author(s):

G.C. Cawley ◽

N.L.C. Talbot

Keyword(s):

Logistic Regression ◽

Model Selection ◽

Kernel Logistic Regression ◽

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Model selection for logistic regression via association rules analysis

Journal of Statistical Computation and Simulation ◽

10.1080/00949655.2012.662231 ◽

2013 ◽

Vol 83 (8) ◽

pp. 1415-1428 ◽

Author(s):

Pannapa Changpetch ◽

Dennis K.J. Lin

Keyword(s):

Logistic Regression ◽

Model Selection ◽

Association Rules ◽

Selection For ◽

Association Rules Analysis

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Bayesian model selection for logistic regression with misclassified outcomes

Statistical Modelling ◽

10.1177/1471082x0700700303 ◽

2007 ◽

Vol 7 (3) ◽

pp. 255-273 ◽

Author(s):

Richard Gerlach ◽

James Stamey

Keyword(s):

Logistic Regression ◽

Model Selection ◽

Bayesian Model ◽

Bayesian Model Selection ◽

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Model selection for logistic regression models

10.1063/1.4756152 ◽

2012 ◽

Author(s):

Christine Duller

Keyword(s):

Logistic Regression ◽

Model Selection ◽

Regression Models ◽

Logistic Regression Models ◽

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Sparse Kernel Logistic Regression using Incremental Feature Selection for Text-Independent Speaker Identification

2006 IEEE Odyssey - The Speaker and Language Recognition Workshop ◽

10.1109/odyssey.2006.248115 ◽

2006 ◽

Author(s):

Marcel Katz ◽

Martin Schaffoner ◽

Edin Andelic ◽

Sven Kruger ◽

Andreas Wendemuth

Keyword(s):

Logistic Regression ◽

Feature Selection ◽

Speaker Identification ◽

Kernel Logistic Regression ◽

Incremental Feature Selection ◽

Selection For ◽

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Logistic Regression Model and Model Selection for Estimating the Risk of Natural Disaster

FORMATH ◽

10.15684/formath.08.009 ◽

2009 ◽

Vol 8 (0) ◽

pp. 137-152

Author(s):

K. Kamo ◽

H. Yanagihara ◽

A. Kato ◽

A. Yoshimoto

Keyword(s):

Logistic Regression ◽

Model Selection ◽

Regression Model ◽

Natural Disaster ◽

Logistic Regression Model ◽

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Bayesian model selection for logistic regression models with random intercept

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2011.06.033 ◽

2012 ◽

Vol 56 (5) ◽

pp. 1256-1274 ◽

Author(s):

Helga Wagner ◽

Christine Duller

Keyword(s):

Logistic Regression ◽

Model Selection ◽

Bayesian Model ◽

Regression Models ◽

Bayesian Model Selection ◽

Logistic Regression Models ◽

Random Intercept ◽

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VARIABLE SELECTION FOR SUPPORT VECTOR MACHINES USING THE GBIC OF THE KERNEL LOGISTIC REGRESSION

Bulletin of informatics and cybernetics ◽

10.5109/25905 ◽

2010 ◽

Vol 42 ◽

pp. 45-54

Author(s):

Ying Jiang ◽

Takashi Yanagawa

Keyword(s):

Logistic Regression ◽

Support Vector Machines ◽

Variable Selection ◽

Support Vector ◽

Kernel Logistic Regression ◽

Vector Machines ◽

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Faculty Opinions recommendation of Model selection for ecologists: the worldviews of AIC and BIC.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718403213.793493662 ◽

2014 ◽

Author(s):

Barry Brook

Keyword(s):

Model Selection ◽

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Earth Model Selection for Computer Simulations

10.21236/ada216843 ◽

1989 ◽

Author(s):

J. J. Pich ◽

S. S. Leroy

Keyword(s):

Model Selection ◽

Computer Simulations ◽

Earth Model ◽

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Chronic Kidney Failure Animal Model Selection for Autonomous Wearable Apparatus for Continuous Peritoneal Dialysis

2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus) ◽

10.1109/elconrus51938.2021.9396676 ◽

2021 ◽

Author(s):

Boris M Putrya ◽

Nikita M. Zhilo ◽

Nikolay A. Bazaev

Keyword(s):

Animal Model ◽

Peritoneal Dialysis ◽

Model Selection ◽

Kidney Failure ◽

Chronic Kidney Failure ◽

Continuous Peritoneal Dialysis ◽

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