What type of normalization does TabularTransform apply to continuous data? I can’t find the answer in the docs.
Here it shows that each continuous variable gets subtracted by its mean and then divided by its standard deviation.
But I was wondering if this is not unnecessary if we do a batchnorm operation in any case, since a batchnorm is a similar scaling but with learnable parameters (if I understand it correctly). Anyone care to share some insight into this?