SHAP (SHapley Additive exPlanations) is a unified approach to explain the output of any machine learning model. SHAP connects game theory with local explanations, uniting several previous methods and representing the only possible consistent and locally accurate additive feature attribution method based on expectations.
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Metadata
3 maintainers
Release files for shap 0.28.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| shap-0.28.0.tar.gz | 221.5 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| shap-0.28.0-cp36-cp36m-macosx_10_7_x86_64.whl | CPython 3.6 | CPython 3.6 pymalloc | macOS 10.7+ x86-64 | Details |
Total release size: 494.1 kB
Release files / shap-0.28.0.tar.gz
| Download URL | shap-0.28.0.tar.gz |
|---|---|
| Size | 221.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
Python-urllib/3.6
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Release files / shap-0.28.0-cp36-cp36m-macosx_10_7_x86_64.whl
| Download URL | shap-0.28.0-cp36-cp36m-macosx_10_7_x86_64.whl |
|---|---|
| Size | 272.5 kB |
| Tags | CPython 3.6 CPython 3.6 pymalloc macOS 10.7+ x86-64 |
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SHA-256 checksum How to use checksums |
8eded4554d126cb4136672320a1906ba6aaf86321ea7d64d60e180fa20bd818c
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BLAKE2b-256 checksum How to use checksums |
a39967b3269a80055e495c257f2e87b2de5c7a7cd2b9f46c85b4ce8302c2447a
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
Python-urllib/3.6
|
Security for shap 0.28.0
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