ScenarioQuestion 1 of 3 / Classic ML0% answeredHow should you handle suspected data leakage in a training pipeline?AKeep the model if offline accuracy is high enough.BRemove features created after the prediction point, rebuild splits by time/entity, and rerun validation.CReduce model complexity until validation accuracy drops to a realistic number.DAdd regularization so the model cannot memorize leaked signals. PreviousNext