randomUniformForest: Random Uniform Forests for Classification, Regression and
Unsupervised Learning
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.
Version: |
1.1.2 |
Depends: |
R (≥ 3.0.0) |
Imports: |
methods, Rcpp (≥ 0.11.1), parallel, doParallel, iterators, foreach (≥ 1.4.2), ggplot2, pROC, gtools, cluster, MASS |
LinkingTo: |
Rcpp |
Suggests: |
R.rsp |
Published: |
2015-01-06 |
Author: |
Saip Ciss |
Maintainer: |
Saip Ciss <saip.ciss at wanadoo.fr> |
License: |
BSD_3_clause + file LICENSE |
NeedsCompilation: |
yes |
Citation: |
randomUniformForest citation info |
Materials: |
NEWS |
CRAN checks: |
randomUniformForest results |
Downloads:
Reverse dependencies: