Nothing
#' Build a random forest based from xdf dataset.
#'
#' Time-stamp: <2017-08-18 12:13:50 Graham Williams>
#'
executeModelRxDForest <- function()
{
# Identify the model specific constants.
TV <- "rf_textview"
NAME <- commonName(crv$RXDFOREST)
PKG <- "RevoScaleR"
FUNC <- "rxDForest"
VAR <- "crs$rf"
TYPE <- Rtxt("Classification")
DESC <- Rtxt("build an xdf based random forest model")
# Check package prerequisites.
if (! packageIsAvailable(PKG, DESC)) return(FALSE)
# Construct the formula for the model build.
crs$target %>%
paste("~", paste(crs$input, collapse=" + ")) %>%
strwrap(crv$log_width, 0, 4) %>%
paste(collapse="\n") ->
frml
# Variables to be included --- a string of indicies.
# included <- getIncludedVariables()
included <- "c(crs$input, crs$target)" # 20110102
# Some convenience booleans
sampling <- not.null(crs$train)
including <- not.null(included)
subsetting <- sampling || including
# Commands.
build.cmd <- paste0(VAR, " <- ", FUNC, "(\n\n ", frml, ",\n\n",
" data = crs$xdf.split[[1]],\n",
" importance = TRUE",
")")
print.cmd <- paste0("print(", VAR, ")")
startLog(NAME)
# Build the model.
appendLog(sprintf(Rtxt("Build the %s model."), NAME), build.cmd)
start.time <- Sys.time()
result <- try(eval(parse(text=build.cmd)), silent=TRUE)
time.taken <- Sys.time() - start.time
# Show the results.
resetTextview(TV)
setTextview(TV,
sprintf(Rtxt("Summary of the %s model for %s (built using '%s'):"),
NAME, TYPE, FUNC),
"\n\n",
collectOutput(print.cmd))
# Now that we have a model, make sure the buttons are sensitive.
showModelRFExists(traditional=TRUE, conditional=FALSE)
# Finish up.
reportTimeTaken(TV, time.taken, NAME)
return(TRUE)
}
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