rare-package: Model path for tree-based lasso framework for selecting rare...

In rare: Linear Model with Tree-Based Lasso Regularization for Rare Features

Description

The package fits the linear model with tree-based lasso regularization proposed in Yan and Bien (2018) using alternating direction method of multipliers (ADMM). The ADMM algorithm is proposed in Algorithm 1 of the same paper. The package also provides tools for tuning regularization parameters, making predictions from the fitted model and visualizing recovered groups of the covariates in a dendrogram.

Details

Its main functions are rarefit, rarefit.cv, rarefit.predict, group.recover and group.plot.

Author(s)

Xiaohan Yan [e-mail], Jacob Bien

References

Yan, X. and Bien, J. (2018) Rare Feature Selection in High Dimensions, https://arxiv.org/abs/1803.06675.

rare documentation built on May 1, 2019, 9:17 p.m.