SODA: Main and Interaction Effects Selection for Discriminant
Analysis and Logistic Regression
Description
Variable and interaction selection are essential to classification in high-dimensional setting. In this package, we provide the implementation of SODA procedure, which is a forward-backward algorithm that selects both main and interaction effects under quadratic discriminant analysis and logistic regression model.