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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...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Egile Nagusiak: Janitza, Silke, Strobl, Carolin, Boulesteix, Anne-Laure
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: BioMed Central 2013
Gaiak:
Sarrera elektronikoa: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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