Algorithms for explaining machine learning models.
Docs: docs.seldon.io/projects/alibi/en/stable/
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Alibi is a source-available Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-quality implementations of black-box, white-box, local and global explanation methods for classification and regression models.
Alibi can be installed from:
With pip
Alibi can be installed from PyPI:
pip install alibi
Alternatively, the development version can be installed:
pip install git+https://github.com/SeldonIO/alibi.git
To take advantage of distributed computation of explanations, install alibi with ray:
pip install alibi[ray]
For SHAP support, install alibi as follows:
pip install alibi[shap]
Method | Models | Explanations | ||||||
---|---|---|---|---|---|---|---|---|
Classification | Regression | Tabular | Text | Images | Categorical features | Train set required | ||
ALE | BB WB | ✔ | ✔ | ✔ | ||||
Partial Dependence | BB WB | ✔ | ✔ | ✔ | ✔ |