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An AUC-based permutation variable importance measure for random forests
BACKGROUND: The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal...
Autores principales: | Janitza, Silke, Strobl, Carolin, Boulesteix, Anne-Laure |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3626572/ https://www.ncbi.nlm.nih.gov/pubmed/23560875 http://dx.doi.org/10.1186/1471-2105-14-119 |
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