A training dataset includes fields that would only become available after the prediction outcome. Evaluation accuracy looks unrealistically high. Which approach best fits?

1. Remove target leakage and rebuild an appropriately timed evaluation split.
2. Profile the source data and compare results with expected constraints.
3. Add business-rule validation for value range and currency consistency.
4. Validate referential relationships and quarantine or resolve orphaned records.