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DESCRIPTION
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DESCRIPTION
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Package: tree.interpreter
Type: Package
Title: Random Forest Prediction Decomposition and Feature Importance Measure
Version: 0.1.1
Date: 2020-01-28
Author: Qingyao Sun
Maintainer: Qingyao Sun <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) <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