Stepwise Predictive Variable Selection for Random Forest

An introduction to several novel predictive variable selection methods for random forest. They are based on various variable importance methods (i.e., averaged variable importance (AVI), and knowledge informed AVI (i.e., KIAVI, and KIAVI2)) and predictive accuracy in stepwise algorithms. For details of the variable selection methods, please see: Li, J., Siwabessy, J., Huang, Z. and Nichol, S. (2019) . Li, J., Alvarez, B., Siwabessy, J., Tran, M., Huang, Z., Przeslawski, R., Radke, L., Howard, F., Nichol, S. (2017). .


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install.packages("steprf")

1.0.2 by Jin Li, 4 years ago


Browse source code at https://github.com/cran/steprf


Authors: Jin Li [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports spm, randomForest, spm2, psy

Suggests knitr, rmarkdown, lattice, reshape2


Imported by stepgbm.


See at CRAN