I fitted a logistic regression model on a data set and got an AUC score of .70. I added some additional out-hot encoded categorical features to the model and the AUC improved slightly to .74.
How do I assess how the model improved? What plots/other analyses are used to to assess the performance gain?
I understand that the model improved, but I want to be able to explain why adding those features improved the model.
This is just a general data science question.