I have a binary classification task on my hands, i have a bunch of people that i need to classify as being ones or zeros and then use predict_proba to estimate how confident my prediction was on the samples used for inference. My understanding is that predict_proba for most classification algorithms isn't accurate and needs to be calibrated. Is there a common approach to get objectively accurate class probabilities ? Algorithms names , techniques and some code if possible. Thanks!
Note : my classes are imbalanced 80/20.