pip install shap==0.40.0
A unified approach to explain the output of any machine learning model.
SourceAmong top 1000 packages on PyPI.
Over 11.5M downloads in the last 90 days.
shap
Based on how often these packages appear together in public
requirements.txt
files on GitHub.
Local Interpretable Model-Agnostic Explanations for machine learning classifiers |
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IBM AI Explainability 360 |
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OSQP: The Operator Splitting QP Solver |
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Fit interpretable machine learning models. Explain blackbox machine learning. |
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Fit interpretable machine learning models. Explain blackbox machine learning. |
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get xtoyed predictions from raw data |
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Kaggle API |
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SAS XPORT file reader |
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Data visualization toolchain based on aggregating into a grid |
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A Component Library for Dash aimed at facilitating network visualization in Python, wrapped around Cytoscape.js |
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Supercharging Machine Learning |
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TensorBoardX lets you watch Tensors Flow without Tensorflow |
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Dash table |
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Relief-based feature selection algorithms |
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Capture C-level output in context managers |
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A high level app and dashboarding solution for Python. |
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A suite of visual analysis and diagnostic tools for machine learning. |
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Menpo library providing tools for 3D Computer Vision research |
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Lightweight pipelining: using Python functions as pipeline jobs. |
shap
Proportion of downloaded versions in the last 3 months (only versions over 1%).
0.39.0 |
46.41% |
0.35.0 |
24.25% |
0.36.0 |
10.17% |
0.40.0 |
8.88% |
0.37.0 |
2.39% |
0.38.1 |
2.07% |
0.34.0 |
1.49% |
0.25.2 |
1.43% |