Which accuracy metric of a ML classifier can maximize map@K of a recommender system for an unbalanced dataset?
If you want to stay in Python, I would suggest going for xgboost instead of GradientBoostingClassifier - among other advantages, it supports map / ndcg as metrics. If you are considering R, gbm supports both map and ndcg.