At the moment I perform the following:
estimators =  estimators.append(('standardize', StandardScaler())) prepare_data = Pipeline(estimators) n_splits = 5 tscv = TimeSeriesSplit(n_splits = n_splits) for train_index, val_index in tscv.split(df_train): X_train, X_val = prepare_data.fit_transform(df_train[train_index]), prepare_data.fit_transform(df_train[val_index]) X_test = prepare_data.fit_transform(df_test)
Now I would like to know if this is correct. My concern is that
X_test are transformed separately. While in the first instance I thought this is how it should be I'm about to change my mind as I think I have to use the
std of the train set to use within the test set?