Department of Image Processing

The question is whether a "weak" learning algorithm that performs just slightly better than random guessing can be “boosted” into an arbitrarily accurate "strong" learning algorithm? Boosting is a general method for improving the accuracy of any given learning algorithm. Focusing primarily on the AdaBoost algorithm, I will present the basic principles and some practical examples.

Main source:
Schapire, R. E. (2001), "The Boosting Approach to Machine Learning: An Overview" , In MSRI Workshop on Nonlinear Estimation and Classification, Berkeley, CA, USA . [https://www.cs.princeton.edu/courses/archive/spring07/cos424/papers/boosting-survey.pdf]