What should your next step be to identify and fix the problem?

You are working on a classification problem with time series data and achieved an area under the receiver operating characteristic curve (AUC ROC) value of 99% for training data after just a few experiments. 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.
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.

Answer: B

Explanation:

https://towardsdatascience.com/time-series-nested-cross-validation-76adba623eb9