I am currently studying about boosting .
boosting-general method of converting rough rules of thumb into highly accurate predication rule.For a given sufficient data ,a boosting algorithm can provably construct single classifier with very high accuracy.
I have studied some advantages of boosting advantages- 1- less error based on ensemble method. 2-suitable if the initial model is pretty bad.
I want to know what are the some of disadvantages of using boosting while creating classification model