Package: MulvariateRandomForestVarImp
Title: Variable Importance Measures for Multivariate Random Forests
Version: 0.0.6
Authors@R: 
    c(person("Nika", "Dogonadze", email = "nika.dogonadze@toptal.com", role = "cre"),
    person("Giles", "Hooker", email = "ghooker@berkeley.edu", role = "aut"),
    person("Vrinda", "Kadiyali", email = "kadiyali@cornell.edu", role = "ctb"),
    person("Sharmistha", "Sikdar", email = "sharmistha.sikdar@tuck.dartmouth.edu", role = "aut"))
Maintainer: Dogonadze Nika <nika.dogonadze@toptal.com>
Description: Calculates two sets of post-hoc variable importance
        measures for multivariate random forests. The first set of
        variable importance measures are given by the sum of mean split
        improvements for splits defined by feature j measured on
        user-defined examples (i.e., training or testing samples). The
        second set of importance measures are calculated on a
        per-outcome variable basis as the sum of mean absolute
        difference of node values for each split defined by feature j
        measured on user-defined examples (i.e., training or testing
        samples). The user can optionally threshold both sets of
        importance measures to include only splits that are
        statistically significant as measured using an F-test.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
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
Depends: R (>= 3.5.0)
Repository: https://megatvini.r-universe.dev
Date/Publication: 2024-09-06 11:16:01 UTC
RemoteUrl: https://github.com/megatvini/vim
RemoteRef: HEAD
RemoteSha: 327ce45e230d1b1f3474de9de7105b0f37a4faeb
NeedsCompilation: no
Packaged: 2026-07-16 07:44:04 UTC; root
Author: Nika Dogonadze [cre],
  Giles Hooker [aut],
  Vrinda Kadiyali [ctb],
  Sharmistha Sikdar [aut]