Glmnet in Python

This is a Python port for the efficient procedures for fitting the entire lasso or elastic-net path for linear regression, logistic and multinomial regression, Poisson regression and the Cox model.

Features include: high efficiency by using coordinate descent with warm starts and active set iterations; methods for prediction, plotting and -fold cross-validation; extensive options such as sparse input-matrix formats and range constraints on coefficients. two recent additions are the multiresponse gaussian, and the grouped multinomial.

License: GPL-2

Published: 2016-10-15

Glmnet for Python (2016) Balakumar, B.J., Hastie, T., Friedman, J., Tibshirani, Simon, N. R. http://hastie.su.domains/glmnet_python/ 

Glmnet in R is also provided for R users, and many bells and whistles in the package are illustrated in the Glmnet Vignette.

Glmnet in Matlab is also available for Matlab users.