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

Jaime L. Speiser; Michael E. Miller; Janet A. Tooze; Edward H. Ip

doi:10.1016/j.eswa.2019.05.028

Keywords

Random forestComputer scienceFeature selectionMachine learningVariable (mathematics)Selection (genetic algorithm)Data miningArtificial intelligenceRandom variableStatisticsMathematics

Affiliated Institutions

Wake Forest University US

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Publication Info

Year: 2019
Type: article
Volume: 134
Pages: 93-101
Citations: 1378
Access: Closed

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APA Style

                            
                                    Jaime L. Speiser, 
                                
                                    Michael E. Miller, 
                                
                                    Janet A. Tooze
                                
                                et al.
                            
                            (2019). 
                            A comparison of random forest variable selection methods for classification prediction modeling. 
                            Expert Systems with Applications
                            , 134
                            
                            , 93-101.
                            https://doi.org/10.1016/j.eswa.2019.05.028

Identifiers

DOI: 10.1016/j.eswa.2019.05.028