randomUniformForest: Random Uniform Forests for Classification and Regression

Ensemble model, for classification and regression, based on a forest of of unpruned and randomized binary 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 Uniform law on the support of each candidate variable. Optimal random node is, then, selected by maximizing information gain (classification) or minimizing 'L2' (or 'L1') distance (regression). Data are either bootstrapped or subsampled for each tree. Random Uniform Forests are aimed to lower correlation between trees, to offer more details about variable importance and selection and to allow native incremental learning.

Version: 1.0.6
Depends: R (≥ 3.0.0)
Imports: methods, Rcpp (≥ 0.11.1), parallel, doParallel, foreach (≥ 1.4.2), ggplot2, pROC, gtools
LinkingTo: Rcpp
Published: 2014-05-29
Author: Saip Ciss
Maintainer: Saip Ciss <saip.ciss at wanadoo.fr>
License: BSD_3_clause + file LICENSE
NeedsCompilation: yes
Citation: randomUniformForest citation info
CRAN checks: randomUniformForest results


Reference manual: randomUniformForest.pdf
Package source: randomUniformForest_1.0.6.tar.gz
Windows binaries: r-devel: randomUniformForest_1.0.6.zip, r-release: randomUniformForest_1.0.6.zip, r-oldrel: randomUniformForest_1.0.6.zip
OS X Snow Leopard binaries: r-release: randomUniformForest_1.0.6.tgz, r-oldrel: randomUniformForest_1.0.6.tgz
OS X Mavericks binaries: r-release: randomUniformForest_1.0.6.tgz