steprf: 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) <doi:10.3390/geosciences9040180>. Li, J., Alvarez, B., Siwabessy, J., Tran, M., Huang, Z., Przeslawski, R., Radke, L., Howard, F., Nichol, S. (2017). <DOI: 10.13140/RG.2.2.27686.22085>.

Getting started

Package details

AuthorJin Li [aut, cre]
MaintainerJin Li <jinli68@gmail.com>
LicenseGPL (>= 2)
Version1.0.2
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("steprf")

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steprf documentation built on June 29, 2022, 5:06 p.m.