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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) <doi:10.48550/arXiv.1906.10845>.

Versions across snapshots

VersionRepositoryFileSize
0.1.3 rolling linux/jammy R-4.5 tree.interpreter_0.1.3.tar.gz 122.6 KiB
0.1.3 rolling linux/noble R-4.5 tree.interpreter_0.1.3.tar.gz 123.9 KiB
0.1.3 rolling source/ R- tree.interpreter_0.1.3.tar.gz 27.0 KiB
0.1.3 latest linux/jammy R-4.5 tree.interpreter_0.1.3.tar.gz 122.6 KiB
0.1.3 latest linux/noble R-4.5 tree.interpreter_0.1.3.tar.gz 123.9 KiB
0.1.3 latest source/ R- tree.interpreter_0.1.3.tar.gz 27.0 KiB
0.1.3 2026-04-26 source/ R- tree.interpreter_0.1.3.tar.gz 27.0 KiB
0.1.3 2026-04-23 source/ R- tree.interpreter_0.1.3.tar.gz 27.0 KiB
0.1.3 2026-04-09 windows/windows R-4.5 tree.interpreter_0.1.3.zip 443.1 KiB
0.1.1 2025-04-20 source/ R- tree.interpreter_0.1.1.tar.gz 28.3 KiB

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