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aVirtualTwins/R/tree.wrapper.R
2015-07-25 02:10:28 +02:00

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R

#' Trees to find Subgroups
#'
#' A wrapper of class VT.tree.xxx
#'
#'
#' See \code{\link{VT.tree}}
#'
#' @param tree.type character "class" for classification tree, "reg" for regression tree
#' @param vt.difft \code{\link{VT.difft}} object
#' @param sens character c(">","<"). See details.
#' @param threshold numeric It can be a unique value or a vector
#'
#' @return \code{VT.tree} or a list of \code{VT.tree} depending on threshold dimension
#'
#' @include tree.R
#'
#' @name vt.tree
#'
#' @export vt.tree
vt.tree <- function(tree.type = "class", vt.difft, sens = ">", threshold = seq(.5, .8, .1), screening = NULL, ...){
if(!inherits(vt.difft, "VT.difft"))
stop("vt.difft parameter must be aVirtualTwins::VT.difft class")
if(is.numeric(threshold)){
if(length(threshold)>1){
res.name <- paste0("tree", 1:length(threshold))
res.list <- lapply(X = threshold, FUN = vt.tree, tree.type = tree.type, vt.difft = vt.difft, sens = sens, screening = screening, ...)
names(res.list) <- res.name
return(res.list)
}else{
if(tree.type == "class")
tree <- aVirtualTwins:::VT.tree.class(vt.difft = vt.difft, sens = sens, threshold = threshold, screening = screening)
else
tree <- aVirtualTwins:::VT.tree.reg(vt.difft = vt.difft, sens = sens, threshold = threshold, screening = screening)
tree$run(...)
return(tree)
}
}else
stop("threshold must be numeric")
}