Random Uniform Forests for Classification, Regression and Unsupervised Learning R package randomUniformForest version 1.1.6 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. Software Depends: R (>= 4.2.0) Imports: methods, Rcpp (>= 0.11.1), parallel, doParallel, iterators, foreach (>= 1.4.2), ggplot2, pROC, cluster, MASS LinkingTo: Rcpp Suggests: R.rsp Saip Ciss <saip.ciss@wanadoo.fr> Comprehensive R Archive Network (CRAN) Saip Ciss BSD_3_clause + file LICENSE (https://CRAN.R-project.org/package=randomUniformForest/LICENSE) 2022-06-21 application/tgz https://CRAN.R-project.org/package=randomUniformForest doi:10.32614/CRAN.package.randomUniformForest