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randomUniformForest

Random Uniform Forests for Classification, Regression and Unsupervised Learning

v1.1.6 · Jun 21, 2022 · BSD_3_clause + file LICENSE

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.

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Maintainer: ‘Saip Ciss <saip.ciss@wanadoo.fr>’

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Maintainer: ‘Saip Ciss <saip.ciss@wanadoo.fr>’

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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Saip Ciss <saip.ciss@wanadoo.fr>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Saip",
                    family = "Ciss",
                    role = c("aut", "cre"),
                    email = "saip.ciss@wanadoo.fr")
as necessary.
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Saip Ciss <saip.ciss@wanadoo.fr>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Saip",
                    family = "Ciss",
                    role = c("aut", "cre"),
                    email = "saip.ciss@wanadoo.fr")
as necessary.

Dependency Network

Dependencies Reverse dependencies Rcpp doParallel iterators foreach ggplot2 pROC cluster MASS randomUniformForest

Version History

new 1.1.6 Mar 9, 2026