The automated notebook pipeline in an AutoML experiment applies StandardScaler to all numerical features in the training dataset as part of the PreProcessor. See below.
But I want a more nuanced and varied treatment of my numeric values (e.g. I have log transforms, winsorization, sigmoid transforms etc etc)
I want to either:
a) Remove all feature engineering / scaling from the automated Preprocessor and have the AutoML notebook run my features as presented to the AutoML experiment.
or
b) Edit the AutoML default pipeline to include a custom PreProcessor script to do more than simply scale every numeric value.
How can i achieve this? I can't seem to find any option to customize this in the UI AutoML Experiment setup and I've got no idea where to find code for the default pipeline that's invoked on every experiment.
