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?

A. Address the model overfitting by using a less complex algorithm and use k-fold cross-validation. B. Address data leakage by applying nested cross-validation during model training. C. Address data leakage by removing features highly correlated with the target value. D. Address the model overfitting by tuning the hyperparameters to reduce the AUC ROC value.