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Comparison of variable selection algorithms on vis-NIR hyperspectral imaging spectra for quantitative monitoring and visualization of bacterial foodborne pathogens in fresh pork muscles

Infrared physics & technology, 2020-06, Vol.107, p.103327, Article 103327

2020

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Practical variable selection for generalized additive models

Computational statistics & data analysis, 2011-07, Vol.55 (7), p.2372-2387

2011

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DPP-VSE: Constructing a variable selection ensemble by determinantal point processes

Expert systems with applications, 2021-09, Vol.178, p.115025, Article 115025

2021

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Bayesian group bridge for bi-level variable selection

Computational statistics & data analysis, 2017-06, Vol.110, p.115-133

2017

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Variable Selection‐based Multivariate Cumulative Sum Control Chart

Quality and reliability engineering international, 2017-04, Vol.33 (3), p.565-578

2017

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Early stopping aggregation in selective variable selection ensembles for high-dimensional linear regression models

Knowledge-based systems, 2018-08, Vol.153, p.1-11

2018

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Randomizing outputs to increase variable selection accuracy

Neurocomputing (Amsterdam), 2016-12, Vol.218, p.91-102

2016

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Use of A Portable Camera for Proximal Soil Sensing with Hyperspectral Image Data

Remote sensing (Basel, Switzerland), 2015-09, Vol.7 (9), p.11434-11448

2015

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A variable selection method based on Tabu search for logistic regression models

European journal of operational research, 2009-12, Vol.199 (2), p.506-511

2009

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On selective learning in stochastic stepwise ensembles

International journal of machine learning and cybernetics, 2020, Vol.11 (1), p.217-230

2020

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Driving Behavior Modeling Based on Consistent Variable Selection in a PWARX Model

Applied sciences, 2021-05, Vol.11 (11), p.4938

2021

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Sparse seemingly unrelated regression modelling: Applications in finance and econometrics

Computational statistics & data analysis, 2010-11, Vol.54 (11), p.2866-2877

Wang, Hao

2010

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Intra-and-inter species biomass prediction in a plantation forest: testing the utility of high spatial resolution spaceborne multispectral RapidEye sensor and advanced machine learning algorithms

Sensors (Basel, Switzerland), 2014-08, Vol.14 (8), p.15348-15370

2014

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Type (I, II) errors variable selection in quantitative structure activity relationships

Chemometrics and intelligent laboratory systems, 2016-03, Vol.152, p.10-17

2016

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Bayesian model selection for logistic regression models with random intercept

Computational statistics & data analysis, 2012-05, Vol.56 (5), p.1256-1274

2012

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Variable Selection in Logistic Regression Model

Chinese Journal of Electronics, 2015-10, Vol.24 (4), p.813-817

2015

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Quantitative detection of apple watercore and soluble solids content by near infrared transmittance spectroscopy

Journal of food engineering, 2020-08, Vol.279, p.109955, Article 109955

2020

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Variable Selection for Efficient Design of Machine Learning-Based Models: Efficient Approaches for Industrial Applications

Engineering Applications of Neural Networks, p.352-366

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A study of variable selection using g-prior distribution with ridge parameter

Computational statistics & data analysis, 2012-06, Vol.56 (6), p.1920-1934

2012

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Variable selection using random forests

Pattern recognition letters, 2010-10, Vol.31 (14), p.2225-2236

2010

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Prediction of holocellulose and lignin content of pulp wood feedstock using near infrared spectroscopy and variable selection

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy, 2020-01, Vol.225, p.117515, Article 117515

2020

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A comparison of random forest variable selection methods for classification prediction modeling

Expert systems with applications, 2019-11, Vol.134, p.93-101

2019

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Application of variable selection and dimension reduction on predictors of MSE’s development

Journal of big data, 2019-02, Vol.6 (1), p.1-44, Article 17

Wubetie, Habtamu Tilaye

2019

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Statistical downscaling of rainfall data using sparse variable selection methods

Environmental modelling & software : with environment data news, 2011-11, Vol.26 (11), p.1363-1371

2011

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A variable selection method based on mutual information and variance inflation factor

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy, 2022-03, Vol.268, p.120652, Article 120652

2022

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Comparison of variable selection algorithms on vis-NIR hyperspectral imaging spectra for quantitative monitoring and visualization of bacterial foodborne pathogens in fresh pork muscles

Practical variable selection for generalized additive models

DPP-VSE: Constructing a variable selection ensemble by determinantal point processes

Bayesian group bridge for bi-level variable selection

Variable Selection‐based Multivariate Cumulative Sum Control Chart

Early stopping aggregation in selective variable selection ensembles for high-dimensional linear regression models

Randomizing outputs to increase variable selection accuracy

Use of A Portable Camera for Proximal Soil Sensing with Hyperspectral Image Data

A variable selection method based on Tabu search for logistic regression models

On selective learning in stochastic stepwise ensembles

Driving Behavior Modeling Based on Consistent Variable Selection in a PWARX Model

Sparse seemingly unrelated regression modelling: Applications in finance and econometrics

Intra-and-inter species biomass prediction in a plantation forest: testing the utility of high spatial resolution spaceborne multispectral RapidEye sensor and advanced machine learning algorithms

Type (I, II) errors variable selection in quantitative structure activity relationships

Bayesian model selection for logistic regression models with random intercept

Variable Selection in Logistic Regression Model

Quantitative detection of apple watercore and soluble solids content by near infrared transmittance spectroscopy

Variable Selection for Efficient Design of Machine Learning-Based Models: Efficient Approaches for Industrial Applications

A study of variable selection using g-prior distribution with ridge parameter

Variable selection using random forests

Prediction of holocellulose and lignin content of pulp wood feedstock using near infrared spectroscopy and variable selection

A comparison of random forest variable selection methods for classification prediction modeling

Application of variable selection and dimension reduction on predictors of MSE’s development

Statistical downscaling of rainfall data using sparse variable selection methods

A variable selection method based on mutual information and variance inflation factor

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