group-lasso
Experiments with coordinate descent in Sparse Group Lasso model
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is group-lasso?
The group-lasso package provides experiments and implementations of the coordinate descent algorithm used in the Sparse Group Lasso model, useful for regression tasks where feature groups are known.
Key differentiator
“group-lasso offers a specialized implementation of the Sparse Group Lasso model, focusing on coordinate descent algorithms for regression tasks with grouped features.”
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 documentation lacks detailed explanations of advanced features and usage scenarios
Coordinate descent algorithm can be slow when processing high-dimensional data, leading to increased computational time
Fit analysis
Who is it for?
✓ Best for
Researchers working with regression models who need to apply regularization at the group level
Data scientists dealing with datasets where features are naturally grouped into meaningful categories
✕ Not a fit for
Projects requiring real-time processing or very large datasets due to computational constraints
Applications that do not benefit from group-level regularization techniques
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
Alternatives
Works well with
Integrations
Next step
Get Started with group-lasso
Step-by-step setup guide with code examples and common gotchas.