TSLA-package

This package provides functions and visualization tools for fitting the
Tree-Guided Rare Feature Selection and Logic Aggregation model.

Implementation of the tree-guided feature selection and logic aggregation approach introduced in Chen et al. (2024) <doi:10.1080/01621459.2024.2326621>. The method enables the selection and aggregation of large-scale rare binary features with a known hierarchical structure using a convex, linearly-constrained regularized regression framework. The package facilitates the application of this method to both linear regression and binary classification problems by solving the optimization problem via the smoothing proximal gradient descent algorithm (Chen et al. (2012) <doi:10.1214/11-AOAS514>).

Jianmin Chen

TSLA

Tree-Guided Rare Feature Selection and Logic Aggregation

Kun Chen

TSLA-package function

Jianmin Chen <a href="/link/jianminc000%40gmail.com?package=TSLA&version=0.1.2" data-mini-rdoc="TSLA::jianminc000@gmail.com">jianminc000@gmail.com</a>, Kun Chen

Author

Tree-Guided Rare Feature Selection and Logic Aggregation — TSLA-package

Jianmin Chen <a href='mailto:jianminc000@gmail.com'>jianminc000@gmail.com</a>, Kun Chen

TSLA-package: Tree-Guided Rare Feature Selection and Logic Aggregation

Description

Arguments

Author