Other packages > Find by keyword >

StratifiedRF  

Builds Trees by Sampling Variables in Groups
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("StratifiedRF", "0.2.2")



Attach the package and use:
library("StratifiedRF")
Maintained by
David Cortes
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-06-21
Latest Update: 2017-06-30
Description:
Random Forest-like tree ensemble that works with groups of predictor variables. When building a tree, a number of variables is taken randomly from each group separately, thus ensuring that it considers variables from each group for the splits. Useful when rows contain information about different things (e.g. user information and product information) and it's not sensible to make a prediction with information from only one group of variables, or when there are far more variables from one group than the other and it's desired to have groups appear evenly on trees. Trees are grown using the C5.0 algorithm rather than the usual CART algorithm. Supports parallelization (multithreaded), missing values in predictors, and categorical variables (without doing One-Hot encoding in the processing). Can also be used to create a regular (non-stratified) Random Forest-like model, but made up of C5.0 trees and with some additional control options. As it's built with C5.0 trees, it works only for classification (not for regression).
How to cite:
David Cortes (2017). StratifiedRF: Builds Trees by Sampling Variables in Groups. R package version 0.2.2, https://cran.r-project.org/web/packages/StratifiedRF. Accessed 16 Jul. 2026.
Previous versions and publish date:
(2026-07-09 08:26), 0.1.1 (2017-06-21 17:25)
Other packages that cited StratifiedRF R package
View StratifiedRF citation profile
Other R packages that StratifiedRF depends, imports, suggests or enhances
Complete documentation for StratifiedRF
Functions, R codes and Examples using the StratifiedRF R package
Some associated functions: predict.stratified_rf . print.stratified_rf . stratified_rf . summary.stratified_rf . varimp_stratified_rf . 
Some associated R codes: rf_c50.R .  Full StratifiedRF package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

schoolmath  
Functions and Datasets for Math Used in School
Contains functions and datasets for math taught in school. A main focus is set to prime-calculation. ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
stevedata  
Steve's Toy Data for Teaching About a Variety of Methodological, Social, and Political Topics
This is a collection of various kinds of data with broad uses for teaching. My students, and academ ...
Download / Learn more Package Citations See dependency  
wordnet  
WordNet Interface
An interface to WordNet using the Jawbone Java API to WordNet. WordNet (< ...
Download / Learn more Package Citations See dependency  
Rnmr1D  
Perform the Complete Processing of a Set of Proton Nuclear Magnetic Resonance Spectra
Perform the complete processing of a set of proton nuclear magnetic resonance spectra from the free ...
Download / Learn more Package Citations See dependency  
tibble  
Simple Data Frames
Provides a 'tbl_df' class (the 'tibble') with stricter checking and better formatting than the tradi ...
Download / Learn more Package Citations See dependency  

27,806

R Packages

239,283

Dependencies

73,837

Author Associations

27,807

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA