Any way to normalize a pipeline output?
I’m wondering if there is any way to normalize (based on training data) the probabilities that come out of a pipeline()?Basically i’d like to try normalize my probabilities based on the training data such that i could say a probability of around 0.5 is about the average likelihood observed during training.I was wondering if there might be any way to do that from within the pipeline() as opposed to having to keep track of whatever i need from the training stats and then running the last post processing step to normalize myself outside of the pipeline as obviously would be a little bit messier to maintain.