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A Machine Learning Specialist is training an XGBoostCNN-based model for detecting fraudulent transactions using Amazon SageMaker AI. The training data contains 5,000 fraudulent behaviors and 500,000 non-fraudulent behaviors. The model reaches an accuracy of 99.5% during training. When tested on the validation dataset, the model shows an accuracy of 99.1% but delivers a high false-negative rate of 87.7%. The Specialist needs to bring down the number of false-negative predictions for the model to be acceptable in production. Which combination of actions must be taken to meet the requirement? (Select TWO.)