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References from Comparing the use of supervised machine learning variable selection methods in the context of two-group classification in the psychological and health sciences. Local targets link to admitted publications; unresolved targets remain external evidence.
Comparative prediction performance with support vector machine and random forest classification techniques
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Applying penalized binary logistic regression with correlation based elastic net for variables selection
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Feature selection using support vector machines and bootstrap methods for ventricular fibrillation detection
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Using exploratory data mining to identify important correlates of nonsuicidal self-injury frequency
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Current sample size conventions: flaws, harms, and alternatives
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Using Bayesian variable selection to identify predictors of psychological functioning post hurricane Irma
10.2139/ssrn.4100137 · 2022 · External reference
Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data
10.1186/1471-2105-12-138 · 2011 · External reference
Data and text mining penalizedSVM: a R-package for feature selection SVM classification
10.1093/bioinformatics/btp286 · 2009 · External reference
Consistent high-dimensional bayesian variable selection via penalized credible regions
10.1080/01621459.2012.716344 · 2012 · External reference
Not all alcohol use disorder criteria are equally severe: toward severity grading of individual criteria in college drinkers
10.1037/adb0000443 · 2019 · External reference
Random forests
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A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis
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Integrating linear discriminant analysis, polynomial basis expansion, and genetic search for two-group classification
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A practical guide to big data research in psychology
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Unresolved reference
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Support-vector networks
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Random Forests for classification in ecology
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Backward, forward and stepwise automated subset selection algorithms: frequency of obtaining authentic and noise variables
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Model selection with lasso-zero: adding straw to the haystack to better find needles
10.1080/10618600.2020.1869026 · 2021 · External reference
Using a genetic algorithm to abbreviate the psychopathic personality inventory-revised (PPI-R)
10.1037/pas0000032 · 2015 · External reference
Random forest-based approach for physiological functional variable selection for driver's stress level classification
10.1007/s10260-018-0423-5 · 2019 · External reference
Statistical predictions with glmnet
10.1186/s13148-019-0730-1 · 2019 · External reference
Comparison of classification methods based on the type of attributes and sample size
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Do we need hundreds of classifiers to solve real world classification problems?
2014 · External reference
Common, uncommon, and novel applications of random forest in psychological research
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Unresolved reference
External reference
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Comparing stochastic optimization methods for variable selection in binary outcome prediction, with application to health policy
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Regularization paths for generalized linear models via coordinate descent
10.18637/jss.v033.i01 · 2010 · External reference
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“Stock market trend prediction using support vector machines and variable selection methods,”in
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Performance improvement of decision tree: a robust classifier using Tabu search algorithm
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Big data in psychology: introduction to the special issue
10.1037/met0000120 · 2016 · External reference
Variable selection—a review and recommendations for the practicing statistician
10.1002/bimj.201700067 · 2018 · External reference
A comparison of two-group classification methods
10.1177/0013164411398357 · 2011 · External reference
Genetic algorithms
10.1038/scientificamerican0792-66 · 1992 · External reference
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10.3390/ijerph192316080 · 2022 · External reference
Comparing partitions
10.1007/bf01908075 · 1985 · External reference
Predicting risk of antenatal depression and anxiety using multi-layer perceptrons and support vector machines
10.3390/jpm11030199 · 2021 · External reference
Variable selection and debiased estimation for single-index expectile model
10.1111/anzs.12348 · 2021 · External reference
Remarks from the new editors
10.3102/1076998610387267 · 2011 · External reference
Linear discriminant functions determined by genetic search
10.1287/ijoc.3.4.345 · 1991 · External reference
Sparse extended redundancy analysis: variable selection via the exclusive LASSO
10.1080/00273171.2019.1694477 · 2021 · External reference
Feature selection with the Boruta package
10.18637/jss.v036.i11 · 2010 · External reference
An efficient elastic net with regression coefficients method for variable selection of spectrum data
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Combinatorial optimization of clustering decisions: an approach to refine psychiatric diagnoses
10.1080/00273171.2020.1717921 · 2021 · External reference
Artificial intelligence in the selection of top-performing athletes for team sports: a proof-of-concept predictive modeling study
10.3390/app15189918 · 2025 · External reference
Efficient and sparse feature selection for biomedical text classification via the elastic net: application to ICU risk stratification from nursing notes
10.1016/j.jbi.2015.02.003 · 2015 · External reference
Using lasso for predictor selection and to assuage overfitting: a method long overlooked in behavioral sciences
10.1080/00273171.2015.1036965 · 2015 · External reference
Evaluating variable selection methods in a classification framework: a simulation study
10.54103/2282-0930/29431 · 2025 · External reference
ShadowVIMP: permutation-based multiple testing-controlled variable selection
10.1186/s12859-026-06412-4 · 2026 · External reference
Using support vector machine to identify imaging biomarkers of neurological and psychiatric disease: a critical review
10.1016/j.neubiorev.2012.01.004 · 2012 · External reference
A variable selection method based on Tabu search for logistic regression models
10.1016/j.ejor.2008.10.007 · 2009 · External reference
Analysis of new variable selection methods for discriminant analysis
10.1016/j.csda.2006.04.019 · 2006 · External reference
A misclassification cost-minimizing evolutionary–neural classification approach
10.1002/nav.20154 · 2006 · External reference
Developing an Indonesia's Health Literacy short-form survey questionnaire (HLS-EU-SQ10-IDN) using the feature selection and genetic algorithm
10.1016/j.cmpb.2019.105047 · 2019 · External reference
Classification and biomarker genes selection for cancer gene expression data using random forest
10.30699/ijp.2017.27990 · 2017 · External reference
A machine learning based variable selection algorithm for binary classification of perinatal mortality
10.1371/journal.pone.0315498 · 2025 · External reference
Using genetic algorithms in a large nationally representative american sample to abbreviate the multidimensional experiential avoidance questionnaire
10.3389/fpsyg.2016.00189 · 2016 · External reference
Deep support vector machines for the identification of stress condition from electrodermal activity
10.1142/s0129065720500318 · 2020 · External reference
Meta-heuristics in short scale construction: ant colony optimization and genetic algorithm
10.1371/journal.pone.0167110 · 2016 · External reference
GA: a package for genetic algorithms in R
10.18637/jss.v053.i04 · 2013 · External reference
Variable selection for categorical response: a comparative study
10.1007/s00180-022-01260-1 · 2023 · External reference
Variable selection for mediators under a Bayesian mediation model
10.1080/10705511.2022.2164285 · 2023 · External reference
Random forest classification of etiologies for an orphan disease
10.1002/sim.6351 · 2015 · External reference
A comparison of random forest variable selection methods for classification prediction modeling
10.1016/j.eswa.2019.05.028 · 2019 · External reference
The importance of covariate selection in controlling for selection bias in observational studies
10.1037/a0018719 · 2010 · External reference
Optimizing feature selection with genetic algorithms: a review of methods and applications
10.1007/s10115-025-02515-1 · 2025 · External reference
Stepwise regression and stepwise discriminant analysis need not apply here: a guidelines editorial
10.1177/0013164495055004001 · 1995 · External reference
Regression shrinkage and selection via the lasso
10.1111/j.2517-6161.1996.tb02080.x · 1996 · External reference
Degrees of freedom in lasso problems
10.1214/12-aos1003 · 2012 · External reference
Variable selection for clinical prediction models in low-dimensional data—a simulation study comparing traditional regression and machine learning methods
10.1186/s12874-026-02930-0 · 2026 · External reference
Evaluation of the lasso and the elastic net in genome-wide association studies
10.3389/fgene.2013.00270 · 2013 · External reference
Predicting adherence to internet-delivered psychotherapy for symptoms of depression and anxiety after myocardial infarction: machine learning insights from the U-CARE heart randomized controlled trial
10.2196/10754 · 2018 · External reference
Why do we still use stepwise modelling in ecology and behaviour?
10.1111/j.1365-2656.2006.01141.x · 2006 · External reference
Performance of using multiple stepwise algorithms for variable selection
10.1002/sim.3943 · 2010 · External reference
Analysis and prediction of students' psychological characteristics of law breaking and crime based on support vector machine algorithm
10.2478/amns-2024-0743 · 2024 · External reference
Classification of MRI and psychological testing data based on support vector machine
2017 · External reference
The abbreviation of personality, or how to measure 200 personality scales with 200 items
10.1016/j.jrp.2010.01.002 · 2010 · External reference
Choosing prediction over explanation in psychology: lessons from machine learning
10.1177/1745691617693393 · 2017 · External reference
Large-scale survey data analysis with penalized regression: a Monte Carlo simulation on missing categorical predictors
10.1080/00273171.2021.1891856 · 2022 · External reference
Regularization and variable selection via the elastic net
10.1111/j.1467-9868.2005.00503.x · 2005 · External reference
On the “degrees of freedom” of the lasso
10.1214/009053607000000127 · 2007 · External reference