SAGE
Global feature importance calculation using Shapley values.
Pricing
See website
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
—Overview
What is SAGE?
SAGE is a tool for calculating global feature importance using Shapley values, providing insights into the impact of features on model predictions. It's essential for understanding and explaining complex models in machine learning projects.
Key differentiator
“SAGE stands out by offering a robust method for calculating global feature importance using Shapley values, which provides a deeper level of insight into the impact of features on model predictions compared to other methods.”
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
Fit analysis
Who is it for?
✓ Best for
Teams working on interpretable machine learning who need global feature importance calculations.
Projects requiring detailed explanations of model behavior and feature impact.
✕ Not a fit for
Real-time applications where quick computation is critical, as Shapley value calculation can be computationally expensive.
Applications that do not require a deep understanding of feature importance or model interpretability.
Cost structure
Pricing
Free Tier
None
Starts at
See website
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with SAGE
Step-by-step setup guide with code examples and common gotchas.