I am using the
caret package in R with the 'C5.0' train method. I am trying to implement kfold cross validation but it is taking too much time to build the model. How can I adjust my parameters so that it takes less time? My train data has 30,000 samples.
#My code train_control <- trainControl(method="repeatedcv", number=10, repeats=3) c50Grid <- expand.grid(.trials = c(1:9, (1:10)*10), .model = c("tree", "rules"), .winnow = c(TRUE, FALSE)) c5Fitvac <- train(y ~ ., data = trainV, method = "C5.0", tuneGrid = c50Grid, trControl = train_control, metric = "Accuracy", importance=TRUE, preProc = c("center", "scale"))