A decision tree memorizes training identifiers, but those identifiers are new at deployment. Which change most directly addresses the modeling flaw?

1. Publish the model before evaluating the revised inputs
2. Increase tree depth until every identifier has its own leaf
3. Remove inappropriate identifier features and validate on representative unseen entities
4. Add the test labels to the training feature table