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randomUniformForest  

Random Uniform Forests for Classification, Regression and Unsupervised Learning
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("randomUniformForest", "1.1.6")



Attach the package and use:
library("randomUniformForest")
Maintained by
Saip Ciss
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-05-29
Latest Update: 2022-06-21
Description:
Ensemble model, for classification, regression and unsupervised learning, based on a forest of unpruned and randomized binary decision trees. Each tree is grown by sampling, with replacement, a set of variables at each node. Each cut-point is generated randomly, according to the continuous Uniform distribution. For each tree, data are either bootstrapped or subsampled. The unsupervised mode introduces clustering, dimension reduction and variable importance, using a three-layer engine. Random Uniform Forests are mainly aimed to lower correlation between trees (or trees residuals), to provide a deep analysis of variable importance and to allow native distributed and incremental learning.
How to cite:
Saip Ciss (2014). randomUniformForest: Random Uniform Forests for Classification, Regression and Unsupervised Learning. R package version 1.1.6, https://cran.r-project.org/web/packages/randomUniformForest. Accessed 15 Jul. 2026.
Previous versions and publish date:
(2026-07-09 06:48), 1.0.6 (2014-05-29 15:22), 1.0.8 (2014-09-19 15:00), 1.0.9 (2014-11-07 16:36), 1.1.0 (2014-11-10 11:48), 1.1.1 (2014-12-04 01:02), 1.1.2 (2015-01-06 05:47), 1.1.5 (2015-02-16 21:29)
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Complete documentation for randomUniformForest
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