## The function is currently defined as
function (data, train, metric = "bayes")
{
probs <- distance(data, train, metric = metric)
if (metric == "bayes") {
best <- apply(probs, 1, max)
}
else if (metric == "mahal") {
best <- apply(probs, 1, min)
}
result <- rep("", length(best))
for (lab in 1:length(train$label)) {
tmp <- probs[, lab] == best
result[tmp] <- train$label[lab]
}
result
}
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