A fraud project scales all rows before splitting training and test data. Why should the pipeline be changed?

1. Keep the workflow because scaling does not involve labels
2. Fit a separate scaler to each individual test request
3. Fit preprocessing on training data and apply it unchanged to held-out data
4. Select the scaler with the best final-test score after many attempts