So I want to perform a predictive model to predict churn.
I have 2 datasets, one with churn and the other without (so I can later perform predictions).
The issue is that I think my Confusion matrix is kinda bad since my target variable is highly unbalanced:
which mostly leads to this confussion matrix:
(Similar values for both logistic regression and decision tree).
This is my workflow:
Is there any way to balance the data? I can't find it in the Orange documentation.