machine-learning-trace-shap amitdhanani2012 · PARTIAL
A game theoretic approach to explain the output of any machine learning model.
github.com/amitdhanani2012/machine-learning-trace-shap · ★ 0 · Forks 0 · Size 267.6 MB
SUMMARY
Technologies 21
Scored 20
Observed 20
Practices 6
Evidence 23
Skips 1
COVERAGE
Analyzed 488 files · 2629 commits · 0 API calls
TECHNOLOGIES & DEPTH
PowerShell LANGUAGE Depth 70
1 files · PRODUCTION
C++ LANGUAGE Depth 70
4 files · PRODUCTION
JavaScript LANGUAGE Depth 70
25 files · PRODUCTION
JSON LANGUAGE Depth 70
3 files · PRODUCTION
Markdown LANGUAGE Depth 70
6 files · PRODUCTION
TOML LANGUAGE Depth 70
1 files · PRODUCTION
YAML LANGUAGE Depth 70
14 files · PRODUCTION
Python LANGUAGE Depth 70
146 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
npm BUILD_TOOL Depth 80
1 files · CONFIGURATION
Poetry BUILD_TOOL Depth 80
1 files · CONFIGURATION
ESLint QUALITY Depth 65
1 files · CONFIGURATION
Lodash LIBRARY Depth 70
4 files · PRODUCTION
NumPy LIBRARY Depth 78
107 files · PRODUCTION, TEST
RabbitMQ MESSAGE_BROKER Depth 81
8 files · CONFIGURATION
React FRAMEWORK Depth 74
5 files · PRODUCTION, TEST
Redis CACHE Depth 69
2 files · CONFIGURATION
Requests LIBRARY Depth —
0 files · config only
TypeScript LANGUAGE Depth 74
8 files · PRODUCTION
pandas LIBRARY Depth 78
36 files · PRODUCTION, TEST
pytest TESTING Depth 74
32 files · PRODUCTION, TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · observedcontainerization · absentlinting · observedformatting · absent
ACTIVITY & OWNERSHIP
First commit 2016-11-22
Last commit 2024-02-06
Active months 76
Commits 2629