predicting new non-standardized data with classifier trained on standardized data
To solve this problem you should use a pipeline. The first stage there is scaling, and the second one is your model. Then you can pickle the whole pipeline and have fun with your new data.
I have some data with say, L features. I have standardized them using StandardScaler() by doing a fit_transform on X_train. Now while predicting, i did clf.predict(scaler.transform(X_test)). So far so good... now if I want to pickle the model for later reuse, how would I go about predicting on the new data in future with this saved model ? the new (future) data will not be standardized and I didn't pickle the scaler.
Is there anything else that I have to do before pickling the model the way I am doing it right now (to be able to predict on non-standardized data)?
reddit post: https://redd.it/4iekc9
Thanks. :)