MLA-C01 Question #175: Real Exam Question with Answer & Explanation

Question

A company is using Amazon SageMaker AI to develop a credit risk assessment model. During model validation, the company finds that the model achieves 82% accuracy on the validation data. However, the model achieved 99% accuracy on the training data. The company needs to address the model accuracy issue before deployment. Which solution will meet this requirement?

Options

• AAdd more dense layers to increase model complexity. Implement batch normalization. Use early
• BImplement dropout layers. Use L1 or L2 regularization. Perform k-fold cross-validation.
• CUse principal component analysis (PCA) to reduce the feature dimensionality. Decrease model
• DAugment the training dataset. Remove duplicate records from the training dataset. Implement