Package: MulvariateRandomForestVarImp
Title: Variable Importance Measures for Multivariate Random Forests
Version: 0.0.1
Authors@R: 
    c(person("Sikdar", "Sharmistha", email = "sharmistha.sikdar@tuck.dartmouth.edu", role = "aut"),
    person("Hooker", "Giles", email = "ghooker@berkeley.edu", role="aut"),
    person("Kadiyali","Vrinda", email = "kadiayali@cornell.edu", role="ctb"),
    person("Dogonadze","Nika", email = "nika.dogonadze@toptal.com", role="cre"))
Description: Calculates post-hoc variable importance measures for multivariate random forests. 
  These are given by split improvement for splits defined by feature j as measured using user-defined (i.e. training or test) examples.
  Importance measures can also be calculated on a per-outcome variable basis using the change in predictions for each split. Both measures can be
  optionally thresholded to include only splits that produce statistically significant changes as measured by an F-test. 
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.1.2
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
Imports: MultivariateRandomForest (>= 1.1.5), MASS (>= 7.3.0)
URL: https://github.com/Megatvini/VIM/
BugReports: https://github.com/Megatvini/VIM/issues
NeedsCompilation: no
Packaged: 2021-12-03 07:45:57 UTC; Nika
Author: Sikdar Sharmistha [aut],
  Hooker Giles [aut],
  Kadiyali Vrinda [ctb],
  Dogonadze Nika [cre]
Maintainer: Dogonadze Nika <nika.dogonadze@toptal.com>
Repository: CRAN
Date/Publication: 2021-12-03 18:50:07 UTC
