A pipeline computes normalization statistics using the complete dataset before splitting into training and test sets. What should change?

1. Fit preprocessing statistics on training data and apply the fitted transformation to held-out data.
2. Fit a separate scaler on each individual test request.
3. Remove the test set and report training accuracy.
4. Use test labels to improve the normalization mean.