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steprf  

Stepwise Predictive Variable Selection for Random Forest
View on CRAN: Click here


Download and install steprf package within the R console
Install from CRAN:
install.packages("steprf")

Install from Github:
library("remotes")
install_github("cran/steprf")

Install by package version:
library("remotes")
install_version("steprf", "1.0.2")



Attach the package and use:
library("steprf")
Maintained by
Jin Li
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-11-08
Latest Update: 2022-06-29
Description:
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>.
How to cite:
Jin Li (2021). steprf: Stepwise Predictive Variable Selection for Random Forest. R package version 1.0.2, https://cran.r-project.org/web/packages/steprf. Accessed 30 Jan. 2025.
Previous versions and publish date:
1.0.0 (2021-11-08 09:40), 1.0.1 (2022-06-18 02:00)
Other packages that cited steprf R package
View steprf citation profile
Other R packages that steprf depends, imports, suggests or enhances
Complete documentation for steprf
Functions, R codes and Examples using the steprf R package
Some associated functions: RFcv2 . cran-comments . steprf . steprfAVI . steprfAVI1 . steprfAVI2 . steprfAVIPredictors . 
Some associated R codes: RFcv2.R . steprf.R . steprfAVI.R . steprfAVI1.R . steprfAVI2.R . steprfAVIPredictors.R .  Full steprf package functions and examples
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