Nothing
#' @importFrom parallel mclapply
#' @importFrom stats as.dist as.formula cutree dlnorm formula hclust lowess median model.matrix na.omit optim pgamma plnorm pnorm predict qnorm runif sd supsmu var wilcox.test
ltrcrfsrc.fast <- function(formula, data,
ntree = 500,
nsplit = 10,
bootstrap = "by.root",
ensemble = "oob",
sampsize = function(x){min(x * .632, max(150, x ^ (3/4)))},
samptype = "swor",
samp = NULL,
ntime = 50,
forest = FALSE,
terminal.qualts = FALSE,
...)
{
## --------------------------------------------------------------
##
## preliminary processing
##
## --------------------------------------------------------------
## verify key options
if (!is.function(sampsize) && !is.numeric(sampsize)) {
stop("sampsize must be a function or number specifying size of subsampled data")
}
##if (is.function(sampsize)) {
## sampsize <- sampsize(nrow(data))
##}
##--------------------------------------------------------------
##
## extract additional options specified by user
## we lock this down to allowed types
##
##--------------------------------------------------------------
## list of forest parameters
rfnames <- names(formals(ltrcrfsrc))
## add key hidden parameters
rfnames <- c(rfnames, "rfq", "perf.type", "gk.quantile", "prob", "prob.epsilon", "vtry")
## restrict to allowed values
rfnames <- rfnames[rfnames != "ntree" &
rfnames != "nsplit" &
rfnames != "bootstrap" &
rfnames != "ensemble" &
rfnames != "sampsize" &
rfnames != "samptype" &
rfnames != "ntime" &
rfnames != "forest" &
rfnames != "terminal.qualts" ]
## get the permissible hidden options
## add formula if present
dots <- list(...)
dots <- dots[names(dots) %in% rfnames]
if (!missing(formula)) {
dots$formula <- formula
}
## set bootstrap accordingly if the user has provided their own sampling
## ntree and sampsize are handled in rfsrc
if (!is.null(samp)) {
bootstrap <- "by.user"
}
##--------------------------------------------------------------
##
## make the grow call and return the object
##
##--------------------------------------------------------------
return(do.call("ltrcrfsrc",
c(list(data = data,
ntree = ntree,
nsplit = nsplit,
bootstrap = bootstrap,
ensemble = ensemble,
sampsize = sampsize,
samptype = samptype,
samp = samp,
ntime = ntime,
terminal.qualts = terminal.qualts,
forest = forest), dots)))
}
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