nalzok/tree.interpreter: Random Forest Prediction Decomposition and Feature Importance Measure

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>.

Getting started

Package details

AuthorQingyao Sun
MaintainerQingyao Sun <sunqingyao19970825@gmail.com>
LicenseMIT + file LICENSE
Version0.1.1
URL https://github.com/nalzok/tree.interpreter
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("nalzok/tree.interpreter")
nalzok/tree.interpreter documentation built on Jan. 29, 2020, 5:48 p.m.