I was doing churn prediction for a company. I've got the following results by applying 3 classifier.
|Decision Tree (pruned)||0.681||0.665|
|Decision Tree unpruned||0.623||0.627|
Now, I want to know two things:
- which model has a better accuracy for a cutoff of 0.9?
As the logistic regression has highest AUC so, in my opinion, Logistic Regression is better
- Which model is the best in terms of ranking the predictions according to their probability of leaving
Can anyone explain how I can interpret them?