To your original question, no, there are not specific rules about how much data to leave out. In the JMP Education analytics courses, we advise you to hold out as much data as you are comfortable with, with at least 20% held out. If you feel the training set is too small to hold back that many rows, consider k-fold cross validation. How many rows are you willing to sacrifice to validation? Use k = n / that many rows. If k < 5 using that formula, consider leave-one-out cross validation.
