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Project description
Effector
Documenation | Global Effect | Regional Effect | API | Tutorials
Effector
is a python package for global and regional effect analysis.
Installation
Effector
is compatible with Python 3.7+
. We recommend to first create a virtual environment with conda
:
conda create -n effector python=3.7
conda activate effector
and then install Effector
via pip
:
pip install effector
Methods and Publications
Methods
Effector
implements the following methods:
Method | Global Effect | Regional Effect |
---|---|---|
PDP | PDP |
RegionalPDP |
d-PDP | DerivativePDP |
RegionalDerivativePDP |
ALE | ALE |
RegionalALE |
RHALE | RHALE |
RegionalRHALE |
SHAP-DP | SHAPDependence |
RegionalSHAP |
Publications
The methods above are based on the following publications:
-
Global Effect:
- PDP and d-PDP: Friedman, Jerome H. "Greedy function approximation: a gradient boosting machine." Annals of statistics (2001): 1189-1232.
- ALE: Apley, Daniel W. "Visualizing the effects of predictor variables in black box supervised learning models." arXiv preprint arXiv:1612.08468 (2016).
- RHALE: Gkolemis, Vasilis, "RHALE
- SHAP-DP: Lundberg, Scott M., and Su-In Lee. "A unified approach to interpreting model predictions." Advances in neural information processing systems. 2017.
-
Regional Effect:
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