Package: vita
Type: Package
Title: Variable importance testing approaches
Version: 0.1
Date: 2015-06-1
Authors@R: person("Ender", "Celik", email = "celik.p.ender@gmail.com",
                  role = c("aut", "cre"))
Author: Ender Celik
Maintainer: Ender Celik <celik.p.ender@gmail.com>
Description: Implements the novel testing approach by Janitza et al.(2015) 
             for the permutation variable importance measure in a random 
             forest and the PIMP-algorithm by Altmann et al.(2010). Janitza 
             et al.(2015) do not use the "standard" permutation variable 
             importance but the cross-validated permutation variable 
             importance for the novel test approach. The cross-validated 
             permutation variable importance is not based on the out-of-bag 
             observations but uses a similar strategy which is inspired by 
             the cross-validation procedure. The novel test approach can be 
             applied for classification trees as well as for regression 
             trees. However, the use of the novel testing approach has not 
             been tested for regression trees so far, so this routine is 
             meant for the expert user only and its current state is rather
             experimental.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.1),parallel,randomForest
LinkingTo: Rcpp
Suggests: mnormt
Built: R 3.1.0; x86_64-w64-mingw32; 2015-10-01 07:15:23 UTC; windows
Archs: i386, x64
