GLMNet
A Julia wrapper for fitting Lasso and ElasticNet GLM models using the glmnet Fortran library.
What is GLMNet?
GLMNet.jl is a Julia package that wraps the glmnet Fortran library to fit Lasso and ElasticNet regularization paths for generalized linear models. It solves problems in high-dimensional statistics by performing feature selection and regularization across linear, logistic, multinomial, Poisson, and Cox models. The package computes entire solution paths efficiently, allowing users to analyze how coefficients change with regularization strength.
Data scientists, statisticians, and researchers working in Julia who need robust regularization methods for regression and classification tasks, particularly those dealing with high-dimensional data or seeking interpretable models through feature selection.
Developers choose GLMNet.jl for its direct interface to the battle-tested glmnet Fortran implementation, ensuring numerical stability and performance. It provides a comprehensive set of GLM families and cross-validation tools within Julia's ecosystem, making it a reliable choice for statistical modeling without sacrificing speed.
Overview
Julia wrapper for fitting Lasso/ElasticNet GLM models using glmnet
Use Cases
Best For
- Fitting regularized linear regression models with Lasso or ElasticNet penalties
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