I have a binary logistic regression that is trained to give a score to an object to see how likely the object will be accepted.What I struggle with is a requirement that if there is a certain flag on the object turned on, then this object must get a score of 1 no matter what. And the model (I think) cannot be trained on existing data (or can?) that this flag is THAT important so it won't give this object any other score but 1.I use xgboost to train my model and wonder what kind of approach should I take with this problem. Maybe I can fake up a field while I'm training the model to make sure that it only appear on accepted objects from the training set?I understand that the requirement violates the whole idea of machine learning, but still would like to hear any suggestions in the field of ML before I think of any other solution.Thank you in advance!
Winner flag on object in logistic regression
machine learning;r;logistic regression;xgboost