Shapley
Quantify classifier value in machine learning ensembles
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is Shapley?
A data-driven framework to quantify the value of classifiers within a machine learning ensemble. Shapley helps understand and optimize the contribution of each model in an ensemble setup.
Key differentiator
“Shapley stands out by providing a clear framework to quantify the value of classifiers in an ensemble, offering insights into model interactions and contributions that are crucial for optimizing machine learning ensembles.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Official docs lack detailed guides on advanced ensemble configurations
Computational complexity increases significantly with more classifiers, impacting real-time applications
Fit analysis
Who is it for?
✓ Best for
Data scientists looking to understand the contribution of individual classifiers in an ensemble setup
Machine learning teams aiming to optimize their ensemble models for better performance and efficiency
✕ Not a fit for
Projects that do not involve machine learning ensembles or classifier evaluation
Teams requiring real-time analysis as Shapley is designed for offline, data-driven evaluations
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Works well with
Integrations
Next step
Get Started with Shapley
Step-by-step setup guide with code examples and common gotchas.