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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) <arXiv:1906.10845>.
Getting started
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Package details |
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| Author | Qingyao Sun |
| Maintainer | Qingyao Sun <sunqingyao19970825@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.1.1 |
| URL | https://github.com/nalzok/tree.interpreter |
| Package repository | View on CRAN |
| Installation |
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