Implements lasso pretraining for generalized linear models for data with grouped observations; data without grouped observations, but with multinomial responses; data with multiple Gaussian responses; and data with repeated measurements over time.
The method fits a lasso model to an initial dataset and then uses its support and coefficient values to guide model fitting for a related task, which can improve performance by leveraging larger datasets and preserve interpretability by identifying features which are generally shared, and which are task specific.
See Craig et al. (2026)