How many folds are ideal for cross validation?
Replying to “How many folds are ideal for cross validation?”:
Often people use 5- or 10-fold depending on sample size. 10-fold CV will be more computationally expensive (e.g. when you run analysis on UKB-RAP)
Replying to “How many folds are ideal for cross validation?”:
The general rule is you should have more folds with a smaller sample size. You could even do a leave-one-individual-out analysis to maximize the training sample size.