What are the disadvantages of boosting



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



Disadvantages of boosting are as follows

1-Time and computation expensive.

2-Hard to implement in real time platform.

3-Complexity of the classification increases.

Hope this helps!