I have a binary classification problem.
The accuracy score is 52%
The precision for 0 is 53% and the precision for 1 is 49%
predict_proba() does this mean my model more accurately predicts when the outcome should be classified zero as opposed to one?
I'm not sure if this is telling me that I should be using the the first value
(ynew) returned from
predict_proba() as opposed to the second
Here is the entire confusion matrix: