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A Comparison of Random Forest Variable Selection Methods for Classification Prediction Modeling
Random forest classification is a popular machine learning method for developing prediction models in many research settings. Often in prediction modeling, a goal is to reduce the number of variables needed to obtain a prediction in order to reduce the burden of data collection and improve efficienc...
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| Publié dans: | Expert Syst Appl |
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| Auteurs principaux: | , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
2019
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7508310/ https://ncbi.nlm.nih.gov/pubmed/32968335 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.eswa.2019.05.028 |
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