Shap-Mini AmirhosseinHonardoust · PARTIAL
A minimal, reproducible explainable-AI demo using SHAP values on tabular data. Trains RandomForest or LogisticRegression models, computes global and local feature importances, and visualizes results through summary and dependence plots, all in under 100 lines of Python.
github.com/AmirhosseinHonardoust/Shap-Mini · ★ 20 · Forks 1 · Size 1.1 MB
SUMMARY
Technologies 7
Scored 6
Observed 6
Practices 6
Evidence 8
Skips 1
COVERAGE
Analyzed 13 files · 3 commits · 0 API calls
TECHNOLOGIES & DEPTH
JSON LANGUAGE Depth 70
2 files · PRODUCTION
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
YAML LANGUAGE Depth 70
1 files · PRODUCTION
Python LANGUAGE Depth 70
3 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth 58
2 files · PRODUCTION
pandas LIBRARY Depth —
0 files · config only
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2025-11-09
Last commit 2025-11-09
Active months 1
Commits 3