PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #87: Real Exam Question with Answer & Explanation

Question

You are working on a classification problem with time series data. After conducting just a few experiments using random cross-validation, you achieved an Area Under the Receiver Operating Characteristic Curve (AUC ROC) value of 99% on the training data. You haven't explored using any sophisticated algorithms or spent any time on hyperparameter tuning. What should your next step be to identify and fix the problem?

Options

• AAddress the model overfitting by using a less complex algorithm and use k-fold cross-validation.
• BAddress data leakage by applying nested cross-validation during model training.
• CAddress data leakage by removing features highly correlated with the target value.
• DAddress the model overfitting by tuning the hyperparameters to reduce the AUC ROC value.