Package: wsrf
Type: Package
Title: Weighted Subspace Random Forest for Classification
Version: 1.5.0
Date: 2015-05-24
Authors@R: c(person("Qinghan", "Meng", role="aut"),
             person("He", "Zhao", email="Simon.Yansen.Zhao@gmail.com", role=c("aut", "cre")),
             person("Graham", "Williams", email="graham.williams@togaware.com", role="aut"),
             person("Junchao", "Lv", role="ctb"),
             person("Baoxun", "Xu", role="aut"))
Maintainer: He Zhao <Simon.Yansen.Zhao@gmail.com>
Description: A parallel implementation of Weighted Subspace Random
    Forest.  The Weighted Subspace Random Forest algorithm was
    proposed in the International Journal of Data Warehousing and
    Mining, 8(2):44-63, 2012, proposed by Baoxun Xu, Joshua Zhexue
    Huang, Graham Williams, Qiang Wang, and Yunming Ye.  The algorithm
    can classify very high-dimensional data with random forests built
    using small subspaces.  A novel variable weighting method is used
    for variable subspace selection in place of the traditional random
    variable sampling.This new approach is particularly useful in
    building models from high-dimensional data.
License: GPL (>= 2)
Depends: R (>= 3.0.0), Rcpp (>= 0.10.2), parallel
LinkingTo: Rcpp
Suggests: rattle (>= 2.6.26), randomForest (>= 4.6.7), party (>=
        1.0.7), stringr (>= 0.6.2), knitr (>= 1.5)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2015-05-24 13:58:57 UTC; simon
Author: Qinghan Meng [aut],
  He Zhao [aut, cre],
  Graham Williams [aut],
  Junchao Lv [ctb],
  Baoxun Xu [aut]
Repository: CRAN
Date/Publication: 2015-05-24 18:56:09
