tree.interpreter: Random Forest Prediction Decomposition and Feature Importance Measure
Qingyao Sun · 2019
An R re-implementation of the 'treeinterpreter' package on PyPI . 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) .