Glmnet in Python

Lasso and elastic-net regularized generalized linear models

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 k-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

Download Glmnet in Python. Currently only the 64-bit linux version is supported.

Citation Info
Glmnet for Python (2016) Balakumar, B.J., Hastie, T., Friedman, J., Tibshirani, Simon, N.
    R. http://www.stanford.edu/~hastie/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.