Model Selection and Testing by the MDL Principle

Information Theory and Statistical Learning ◽

10.1007/978-0-387-84816-7_2 ◽

2008 ◽

pp. 25-43 ◽

Author(s):

Jorma Rissanen

Keyword(s):

Model Selection ◽

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Model Selection Using Information Theory and the MDL Principle

Sociological Methods & Research ◽

10.1177/0049124103262064 ◽

2004 ◽

Vol 33 (2) ◽

pp. 230-260 ◽

Author(s):

Robert A. Stine

Keyword(s):

Information Theory ◽

Model Selection ◽

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ON SUITABLE MODEL SELECTION APPROACH FOR ANALYSIS OF MENTAL HEALTH SERVICE USE DATA

IAPQR TRANSACTIONS ◽

10.32381/iapqrt.2019.43.02.6 ◽

2019 ◽

Vol 43 (2) ◽

pp. 212-222

Author(s):

DULAL K. BHAUMIK ◽

◽

SUBHASH ARYAL ◽

SCOTT HUR ◽

◽

...

Keyword(s):

Mental Health ◽

Mental Health Service ◽

Model Selection ◽

Health Service ◽

Service Use ◽

Mental Health Service Use ◽

Health Service Use ◽

Suitable Model ◽

Model Selection Approach ◽

Selection Approach

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A Teaching Note for Model Selection and Validation

Mathematical Journal of Interdisciplinary Sciences ◽

10.15415/mjis.2013.12012 ◽

2013 ◽

Vol 1 (2) ◽

pp. 55-62 ◽

Author(s):

K. Muralidharan

Keyword(s):

Model Selection

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A Diagnostic Framework for "Bashed" Wells in Unconventional Reservoirs: A Numerical Simulation and Model Selection Theory Approach

Proceedings of the 4th Unconventional Resources Technology Conference ◽

10.15530/urtec-2016-2448463 ◽

2016 ◽

Author(s):

L. Zhe ◽

R. Younis ◽

J. Jiang

Keyword(s):

Numerical Simulation ◽

Model Selection ◽

Unconventional Reservoirs ◽

Theory Approach ◽

Selection Theory ◽

Diagnostic Framework

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A Model Selection Approach to the Two-Phase Regression Estimation and The Human Sensitivity Analysis in Urban Ecosystem

Behaviormetrika ◽

10.2333/bhmk.10.13_1 ◽

1983 ◽

Vol 10 (13) ◽

pp. 1-18

Author(s):

Masashi Itoh ◽

Kazuo Noda ◽

Yutaka Shinada ◽

Naomi Tachibana

Keyword(s):

Sensitivity Analysis ◽

Model Selection ◽

Urban Ecosystem ◽

Regression Estimation ◽

Two Phase ◽

Model Selection Approach ◽

Selection Approach

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Lakes Marion-Moultrie stream system investigation: Part I- Model selection, calibration, and error analysis

10.3133/wri7425 ◽

1974 ◽

Keyword(s):

Model Selection ◽

Error Analysis ◽

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Deep Learning Model Selection of Suboptimal Complexity

Автоматика и телемеханика ◽

10.31857/s000523100001252-1 ◽

2018 ◽

pp. 129-147

Author(s):

Oleg Bakhteev ◽

◽

Vadim Strijov ◽

Keyword(s):

Deep Learning ◽

Model Selection ◽

Learning Model ◽

Deep Learning Model ◽

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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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Model selection of extreme learning machine based on latent feature space

Journal of Computer Applications ◽

10.3724/sp.j.1087.2013.01600 ◽

2013 ◽

Vol 33 (6) ◽

pp. 1600-1603

Author(s):

Wentao MAO ◽

Zhongtang ZHAO ◽

Huanhuan HE

Keyword(s):

Model Selection ◽

Extreme Learning Machine ◽

Feature Space ◽

Learning Machine ◽

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Model selection based on particle swarm optimization for omics data classification

JOURNAL OF SHENZHEN UNIVERSITY SCIENCE AND ENGINEERING ◽

10.3724/sp.j.1249.2016.03264 ◽

2016 ◽

Vol 33 (3) ◽

pp. 264 ◽

Author(s):

Junshan Yang ◽

Zhen Ji ◽

Weixin Xie ◽

Zexuan Zhu

Keyword(s):

Particle Swarm Optimization ◽

Model Selection ◽

Particle Swarm ◽

Data Classification ◽

Swarm Optimization

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