Nothing
classscatter <-
function(formula, data, method, col.correct = "black",
col.wrong = "red", gs = NULL, ...)
{
variables <- dimnames(attributes(terms(formula, data=data))$factors)[[1]]
response <- variables[1]
discriminators <- variables[-1]
if(any(discriminators == ".")) {
exclude <- c(response, discriminators[discriminators != "."])
discriminators <- colnames(data)[!is.element(colnames(data), exclude)]
}
x <- data[, discriminators]
grouping <- data[ , response]
result <- do.call(method, list(x, grouping, ...))
pr <- predict(result, x)
if (is.list(pr)) pr <- pr$class
nc <- pr != grouping
color <- rep(col.correct, length(grouping))
color[nc] <- col.wrong
if (is.null(gs)) gs <- as.character(grouping)
plot(x, col = color, pch = gs, ...)
return(mean(nc))
}
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