I want to create a custom classification model which also involves transformation of dataset. However, while performing the dataset transformation, the size of transformations increase rapidly. To tackle with this situation, I want to do sampling on training set, however, the test set cannot be sampled for obvious reason.
I'm not able to understand, what can I do with sklearn Pipeline method to handle this situation.