How predict_proba in sklearn produces two columns? what are their significance?
We can distinguish between the classifiers using the classifier classes. if the classifier name is model then model.classes_ will give the distinct classes.
I was using simple logistic regression to predict  a problem and trying to plot the precision_recall_curve and the roc_curve with predict_proba(X_test). I checked the docstring of predict_proba but hadn't had much details on how it works. I was having bad input every time and checked that y_test, predict_proba(X_test) doesn't match. Finally discovered predict_proba() produces 2 columns and people use the second.
It would be really helpful if someone can give an explanation how it produces two columns and their significance. TIA.