Hello everyone i'm new to data science world. So i want to know if my model is overfitting. Usually i'm comparing training accuracy and testing accuracy. But on some reference many people using roc_auc score from training and testing and compared it to know if the model is overfit.
Which metrics evaluation better? I have imbalanced data, but already using SMOTE oversampling.
The second question i want to ask if i'm decided to use accuracy method to know if my model is overfitting, should i try using k cross validation with scoring='accuracy' to prove more?