Adding penalties to number of splits in Partition platform to reduce number of leaves?
I have recently been spending a lot of time in the Partition platform, and currently I'm looking for a way to automate the analyses. My issue is this: generally I've been splitting the data set 50/50 training/validation, and hitting "Go", which maximizes the validation RSquare. But, this often leads to models which have a larger number of splits than are really credible, e.g. here where it creates...