PABannier/sparseglm

Fast and modular solver for sparse generalized linear models

21
/ 100
Experimental

This helps data scientists and machine learning engineers quickly build and train models that can handle large datasets with many features, even if most of those features aren't relevant. It takes in your dataset (features and target variable) and outputs a set of coefficients that tell you which features are most important for predicting the target, efficiently handling both dense and sparse data.

No commits in the last 6 months.

Use this if you need to build predictive models like Lasso or Elastic-Net and want a very fast and memory-efficient solution that can scale to millions of data points and features.

Not ideal if you are looking for a simple, off-the-shelf Python library for basic GLM tasks and don't require high performance on very large, sparse datasets.

predictive-modeling feature-selection large-scale-data statistical-learning sparse-data-analysis
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

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Stars

8

Forks

Language

Rust

License

MIT

Last pushed

Sep 29, 2024

Monthly downloads

2

Commits (30d)

0

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