Thresholding Gini variable importance with a single-trained random forest: An empirical Bayes approach

Author:

Dunne RobertORCID,Reguant RocORCID,Ramarao-Milne Priya,Szul Piotr,Sng Letitia M.F.,Lundberg Mischa,Twine Natalie A.,Bauer Denis C.

Funder

CSIRO

Publisher

Elsevier BV

Subject

Computer Science Applications,Genetics,Biochemistry,Structural Biology,Biophysics,Biotechnology

Reference38 articles.

1. Lundberg S.M., Erion G.G., Lee S.-I. Consistent Individualized Feature Attribution for Tree Ensembles. ArXiv180203888 Cs Stat 2019.

2. VariantSpark: cloud-based machine learning for association study of complex phenotype and large-scale genomic data;Bayat;GigaScience,2020

3. On the overestimation of random forest’s out-of-bag error;Janitza;PLOS ONE,2018

4. Variable importance assessment in regression: linear regression versus random forest;Grömping;Am Stat,2009

5. A unified approach to interpreting model predictions;Lundberg;Adv Neural Inf Process Syst,2017

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