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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...
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| Main Authors: | , , |
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| Format: | Artigo |
| Language: | Inglês |
| Published: |
BioMed Central
2013
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3626572/ https://ncbi.nlm.nih.gov/pubmed/23560875 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-14-119 |
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