Boosting is a general method to improve the accuracy of any givenlearning algorithm. I will introduce a new method of boosting - AdaBoost- and discuss its advantages compared to other traditional methods of boosting like "boost-by-majority" algorithm. I will also try to give an intuitive explanation as to why boosting does not suffer from overfitting.

Reference:
http://link.springer.com/chapter/10.1007%2F3-540-59119-2_166?LI=true