group-lasso

Experiments with coordinate descent in Sparse Group Lasso model

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

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

Strength Radar

Implementation o…Supports both sp…Optimized for re…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Implementation of coordinate descent for Sparse Group Lasso

Supports both sparse and dense data formats

Optimized for regression tasks with known feature groups

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

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Alternatives

Next step

Get Started with group-lasso

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →