Identifying Informative Predictor Variables With Random Forests
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DOI: 10.3102/10769986231193327
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References listed on IDEAS
- Kursa, Miron B. & Rudnicki, Witold R., 2010. "Feature Selection with the Boruta Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i11).
- Hapfelmeier, A. & Ulm, K., 2013. "A new variable selection approach using Random Forests," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 50-69.
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- Leogrande, Angelo, 2024. "Strategie innovative per la logistica: il valore del kitting e assembly nel settore idrotermosanitario," MPRA Paper 122746, University Library of Munich, Germany.
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Keywords
random forest; variable importance; interpretable machine learning; recursive partitioning; variable selection;All these keywords.
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