R/accSDA.R

#' accSDA: A package for performing sparse discriminant analysis
#'         in various ways.
#'
#' 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 \code{\link{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.
#'
#'
#' @docType package
#' @name accSDA
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accSDA documentation built on May 2, 2019, 5:42 a.m.