Subset selection for multiple linear regression via optimization

Journal of Global Optimization ◽

10.1007/s10898-020-00876-1 ◽

2020 ◽

Vol 77 (3) ◽

pp. 543-574 ◽

Author(s):

Young Woong Park ◽

Diego Klabjan

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Subset Selection ◽

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A MORE GENERAL CRITERION FOR SUBSET SELECTION IN MULTIPLE LINEAR REGRESSION

Communication in Statistics- Theory and Methods ◽

10.1081/sta-120003653 ◽

2002 ◽

Vol 31 (5) ◽

pp. 795-811 ◽

Author(s):

D. N. Kashid ◽

S. R. Kulkarni

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Subset Selection ◽

General Criterion

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A mathematical programming approach for integrated multiple linear regression subset selection and validation

Pattern Recognition ◽

10.1016/j.patcog.2020.107565 ◽

2020 ◽

Vol 108 ◽

pp. 107565

Author(s):

Seokhyun Chung ◽

Young Woong Park ◽

Taesu Cheong

Keyword(s):

Linear Regression ◽

Mathematical Programming ◽

Multiple Linear Regression ◽

Subset Selection ◽

Programming Approach ◽

Mathematical Programming Approach

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Budget constrained model selection for multiple linear regression

Communications in Statistics - Simulation and Computation ◽

10.1080/03610918.2021.1991956 ◽

2021 ◽

pp. 1-13

Author(s):

Jingying Zhang ◽

Ronald L. Rardin ◽

Justin R. Chimka

Keyword(s):

Model Selection ◽

Linear Regression ◽

Multiple Linear Regression ◽

Constrained Model ◽

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Subset selection in multiple linear regression models: A hybrid of genetic and simulated annealing algorithms

Applied Mathematics and Computation ◽

10.1016/j.amc.2013.05.016 ◽

2013 ◽

Vol 219 (23) ◽

pp. 11018-11028 ◽

Author(s):

H. Hasan Örkcü

Keyword(s):

Simulated Annealing ◽

Linear Regression ◽

Multiple Linear Regression ◽

Regression Models ◽

Subset Selection ◽

Linear Regression Models ◽

Annealing Algorithms ◽

Multiple Linear Regression Models

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Subset selection in multiple linear regression in the presence of outlier and multicollinearity

Statistical Methodology ◽

10.1016/j.stamet.2014.02.002 ◽

2014 ◽

Vol 19 ◽

pp. 44-59 ◽

Author(s):

Nileshkumar H. Jadhav ◽

Dattatraya N. Kashid ◽

Subhash R. Kulkarni

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Subset Selection

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Subset selection in multiple linear regression: a new mathematical programming approach

Computers & Industrial Engineering ◽

10.1016/j.cie.2005.03.004 ◽

2005 ◽

Vol 49 (1) ◽

pp. 155-167 ◽

Author(s):

Burak Eksioglu ◽

Riza Demirer ◽

Ismail Capar

Keyword(s):

Linear Regression ◽

Mathematical Programming ◽

Multiple Linear Regression ◽

Subset Selection ◽

Programming Approach ◽

Mathematical Programming Approach

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MLR-tagging: informative SNP selection for unphased genotypes based on multiple linear regression

Bioinformatics ◽

10.1093/bioinformatics/btl420 ◽

2006 ◽

Vol 22 (20) ◽

pp. 2558-2561 ◽

Author(s):

J. He ◽

A. Zelikovsky

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

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Subset selection in multiple linear regression: An improved Tabu search

Journal of the Korean Society of Marine Engineering ◽

10.5916/jkosme.2016.40.2.138 ◽

2016 ◽

Vol 40 (2) ◽

pp. 138-145 ◽

Author(s):

Jaegug Bae ◽

Jung-Tae Kim ◽

Jae-Hwan Kim

Keyword(s):

Linear Regression ◽

Tabu Search ◽

Multiple Linear Regression ◽

Subset Selection

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Group subset selection for linear regression

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2014.02.005 ◽

2014 ◽

Vol 75 ◽

pp. 39-52 ◽

Author(s):

Yi Guo ◽

Mark Berman ◽

Junbin Gao

Keyword(s):

Linear Regression ◽

Subset Selection ◽

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Optimal feature selection for predicting soil CEC: Comparing the hybrid of ant colony organization algorithm and adaptive network-based fuzzy system with multiple linear regression

Geoderma ◽

10.1016/j.geoderma.2017.03.010 ◽

2017 ◽

Vol 298 ◽

pp. 27-34 ◽

Author(s):

Hosein Shekofteh ◽

Fatemeh Ramazani ◽

Hossein Shirani

Keyword(s):

Feature Selection ◽

Linear Regression ◽

Multiple Linear Regression ◽

Fuzzy System ◽

Adaptive Network ◽

Optimal Feature Selection ◽

Selection For ◽

Optimal Feature

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