#' Plot Local Expert summary function
#'
#' This function allows a user to quickly visualize the performance of a tuning /
#' method configuration for a local expert list by plotting the average
#' accuracy and kappa values from the resamples of local experts, in addition
#' to the standard deviation of these metrics.
#'
#'
#' @param model.info A model information object created using the
#' \code{\link{ExtractModelInfo}} function
#' @export
#'
PlotLEs <- function(model.info){
# save and reset default graphical parameters
opar <- par(no.readonly = TRUE)
on.exit(par(opar))
# change plotting window to 2x2
par(mfrow = c(2,2))
# first plot
par(mar = c(0, 4.1, 2.1, 1.1))
plot(model.info$performance$accuracy, xaxt = 'n', xlab = '', ylab = 'accuracy', pch = 16)
# second plot
par(mar = c(0, 3.8, 2.1, 2.1))
plot(model.info$performance$kappa, xaxt = 'n', xlab = '', ylab = 'kappa', pch = 17)
# third plot
par(mar = c(4, 4.1, 2.1, 1.1))
plot(model.info$performance$accuracySD, ylab = 'accuracy stdev', xlab = 'Local Experts', pch = 16)
# fourth plot
par(mar = c(4, 3.8, 2.1, 2.1))
plot(model.info$performance$kappaSD, ylab = 'kappa stdev', xlab = 'Local Experts', pch = 17)
# summarize output
cat(paste("The maximum accuracy is",
format(max(model.info$performance$accuracy), digits = 3), "\n"))
cat(paste("The average accuracy is",
format(mean(model.info$performance$accuracy), digits = 3), "\n"))
cat(paste("The minimum kappa is",
format(min(model.info$performance$kappa), digits = 3), "\n"))
cat(paste("The average kappa is",
format(mean(model.info$performance$kappa), digits = 3), "\n\n"))
}
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