Package: rerf
Type: Package
Title: Randomer Forest
Version: 1.1.2
Date: 2018-07-05
Authors@R: c(person("James", "Browne", role = c("aut", "cre"),
	   	    email = "jbrowne6@jhu.edu"),
	     person("Tyler", "Tomita", role = "aut",
	            email = "ttomita2@jhmi.edu"),
	     person("Joshua", "Vogelstein", role = "ths",
	     	    email = "jovo@jhu.edu"))
Description: Random Forester (RerF) is an algorithm developed by Tomita
  (2016) <arXiv:1506.03410v2> which is similar to Random Forest - Random
  Combination (Forest-RC) developed by Breiman (2001)
  <doi:10.1023/A:1010933404324>.  Random Forests create axis-parallel, or
  orthogonal trees. That is, the feature space is recursively split along
  directions parallel to the axes of the feature space. Thus, in cases in
  which the classes seem inseparable along any single dimension, Random
  Forests may be suboptimal.  To address this, Breiman also proposed and
  characterized Forest-RC, which uses linear combinations of coordinates
  rather than individual coordinates, to split along.  This package,
  'rerf', implements RerF which is similar to Forest-RC.  The difference
  between the two algorithms is where the random linear combinations
  occur: Forest-RC combines features at the per tree level whereas RerF
  takes linear combinations of coordinates at every node in the tree.
License: GPL-2
URL: https://github.com/neurodata/R-RerF
Imports: parallel, RcppZiggurat, utils, stats, dummies
LinkingTo: Rcpp, RcppArmadillo
SystemRequirements: GNU make
ByteCompile: true
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-07-15 21:48:09 UTC; james
Author: James Browne [aut, cre],
  Tyler Tomita [aut],
  Joshua Vogelstein [ths]
Maintainer: James Browne <jbrowne6@jhu.edu>
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2018-07-16 06:10:03 UTC
