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We provide extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression (gaussian), multi-task gaussian, logistic and multinomial regression models (grouped or not), Poisson regression and the Cox model. The algorithm uses cyclical coordinate descent in a path-wise fashion. Details may be found in Friedman, Hastie, and Tibshirani (2010), Simon et al. (2011), Tibshirani et al. (2012), Simon, Friedman, and Hastie (2013).
Version 3.0 is a major release with several new features, including:
cv.glmnet, as well as confusion matrices and ROC plots for
classification models;x input matrix for
glmnet that allow for one-hot-encoding of factor
variables, appropriate treatment of missing values, and an option to
create a sparse matrix if appropriate.glmnet.Version 4.0 is a major release that allows for any GLM family, besides the built-in families.
Version 4.1 is a major release that expands the scope for survival
modeling, allowing for (start, stop) data, strata, and sparse X inputs.
It also provides a much-requested method for
survival:survfit.
Friedman, Jerome, Trevor Hastie, and Robert Tibshirani. 2010. “Regularization Paths for Generalized Linear Models via Coordinate Descent.” Journal of Statistical Software, Articles 33 (1): 1–22. https://doi.org/10.18637/jss.v033.i01.
Simon, Noah, Jerome Friedman, and Trevor Hastie. 2013. “A Blockwise Descent Algorithm for Group-Penalized Multiresponse and Multinomial Regression.”
Simon, Noah, Jerome Friedman, Trevor Hastie, and Robert Tibshirani. 2011. “Regularization Paths for Cox’s Proportional Hazards Model via Coordinate Descent.” Journal of Statistical Software, Articles 39 (5): 1–13. https://doi.org/10.18637/jss.v039.i05.
Tibshirani, Robert, Jacob Bien, Jerome Friedman, Trevor Hastie, Noah Simon, Jonathan Taylor, and Ryan Tibshirani. 2012. “Strong Rules for Discarding Predictors in Lasso-Type Problems.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 74 (2): 245–66. https://doi.org/10.1111/j.1467-9868.2011.01004.x.
Kenneth Tay, J, Narasimhan, Balasubramanian, Hastie, Trevor. 2023. “Elastic Net Regularization Paths for All Generalized Linear Models.” Journal of Statistical Software, Articles 106 (1): 1–31. https://doi.org/10.18637/jss.v106.i01.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.