accSDA: accSDA: A package for performing sparse discriminant analysis...

Description

Description

The accSDA package provides functions to perform sparse discriminant analysis using a selection of three optimization methods, proximal gradient (PG), accelerated proximal gradient (APG) and alternating direction method of multipliers (ADMM). The package is intended to extend the available tools to perform sparse discriminant analysis in R. The three methods can be called from the function ASDA. Cross validation is also implemented for the L1 regularization parameter. Functions for doing predictions, summary, printing and simple plotting are also provided. The sparse discriminant functions perform lda on the projected data by default, using the lda function in the MASS package. The functions return an object of the same class as the name of the function and provide the lda solution, along with the projected data, thus other kinds of classification algorithms can be employed on the projected data.


accSDA documentation built on May 2, 2019, 5:42 a.m.