IM
csinva/imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
1.6k 137 +0/wk
GitHub
ai artificial-intelligence bayesian-rule-list data-science explainable-ai explainable-ml imodels interpretability machine-learning ml optimal-classification-tree python
Trend
3
Star & Fork Trend (19 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
csinva/imodels has +0 stars this period . 7-day velocity: 0.1%.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | imodels | Enzyme | testkube | yt-channels-DS-AI-ML-CS |
|---|---|---|---|---|
| Stars | 1.6k | 1.6k | 1.6k | 1.6k |
| Forks | 137 | 157 | 157 | 155 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Jupyter Notebook | LLVM | Go Template | N/A |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | NOASSERTION | NOASSERTION | N/A |
Capability Radar vs Enzyme
imodels
Enzyme
Maintenance Activity 79
Last code push 43 days ago.
Community Engagement 43
Fork-to-star ratio: 8.7%. Lower fork ratio may indicate passive usage.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.