Package: tree.interpreter
Type: Package
Title: Random Forest Prediction Decomposition and Feature Importance
        Measure
Version: 0.1.3
Date: 2025-09-18
Authors@R: person(given = "Qingyao",
                  family = "Sun",
                  role = c("aut", "cre"),
                  email = "sunqingyao19970825@gmail.com")
Description: An R re-implementation of the 'treeinterpreter' package on PyPI
        <https://pypi.org/project/treeinterpreter/>. Each prediction can be
        decomposed as 'prediction = bias + feature_1_contribution + ... +
        feature_n_contribution'. This decomposition is then used to calculate
        the Mean Decrease Impurity (MDI) and Mean Decrease Impurity using
        out-of-bag samples (MDI-oob) feature importance measures based on the
        work of Li et al. (2019) <doi:10.48550/arXiv.1906.10845>.
Encoding: UTF-8
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.2)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.0.2
Suggests: MASS, randomForest, ranger, testthat (>= 2.1.0), knitr,
        rmarkdown, covr
URL: https://github.com/nalzok/tree.interpreter
BugReports: https://github.com/nalzok/tree.interpreter/issues
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2025-09-18 11:49:28 UTC; qingyao
Author: Qingyao Sun [aut, cre]
Maintainer: Qingyao Sun <sunqingyao19970825@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-18 12:10:02 UTC
Built: R 4.6.0; x86_64-w64-mingw32; 2025-11-02 03:22:44 UTC; windows
Archs: x64
