It's easy to tune model hyperparameters in pycaret with tune_model but how are you supposed to tune the data preprocessing hyperparameters?
You need to call setup before you create a model but it is in setup where you define these values.
Let's say I want to compare the effects of standardizing my data vs. normalizing it. Is there a way to do this built into pycaret? I could write my own loops or processing pipelines... but that seems to against the low-code ethos of the library...
