wan-huiyan/ml-feature-evaluator
Structured 10-step diagnostic for go/no-go feature evaluation in production ML pipelines. Covers outcome gradient, coverage gaps, entropy/gain ratio, conditional MI, incremental CV AUC, and 9-point temporal safety. Claude Code skill.
Stars
—
Forks
—
Language
—
License
MIT
Category
Last pushed
Mar 20, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/wan-huiyan/ml-feature-evaluator"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
online-ml/river
🌊 Online machine learning in Python
IFCA-Advanced-Computing/frouros
Frouros: an open-source Python library for drift detection in machine learning systems.
NannyML/nannyml
nannyml: post-deployment data science in python
Western-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch...
mitre/menelaus
Online and batch-based concept and data drift detection algorithms to monitor and maintain ML...