I don't know why you would want to do this but you can make your own summary function:
library(caret)
set.seed(1)
dat <- twoClassSim(100)
foo <- function(data, lev = NULL, model = NULL) {
probs <- data[, lev[1]]
c(rmse = RMSE(pred = probs,
obs = ifelse(data$obs == lev[1], 1, 0)))
}
ctrl <- trainControl(classProbs = TRUE,
summaryFunction = foo)
set.seed(2)
mod <- train(Class ~ ., data = dat,
method = "lda",
metric = "rmse",
minimize = TRUE,
trControl = ctrl)
Max