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LAMDA-NJU/Deep-Forest
An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)
962 167 +0/wk
GitHub
deep-forest ensemble-learning machine-learning python random-forest
Trend
0
Star & Fork Trend (19 data points)
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LAMDA-NJU/Deep-Forest has +0 stars this period . Velocity data will be available after more historical data is collected.
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| Metric | Deep-Forest | tf-lite-unity-sample | cookbook-2nd | Ultimate-Data-Science-Toolkit---From-Python-Basics-to-GenerativeAI |
|---|---|---|---|---|
| Stars | 962 | 963 | 961 | 963 |
| Forks | 167 | 267 | 257 | 331 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | C# | Python | Jupyter Notebook |
| Sources | 1 | 1 | 1 | 1 |
| License | NOASSERTION | N/A | NOASSERTION | GPL-3.0 |
Capability Radar vs tf-lite-unity-sample
Deep-Forest
tf-lite-unity-sample
Maintenance Activity 0
Last code push 207 days ago.
Community Engagement 87
Fork-to-star ratio: 17.4%. Active community forking and contributing.
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 30
No clear license detected — proceed with caution.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.