Boosting


Boosting is based on the idea of combining weak learners to create a strong learner (classifier). A weak learner is defined to be a classifier which is only slightly correlated with the true classification (it can label examples better than random guessing). In contrast, a strong learner is a classifier that is arbitrarily well-correlated with the true classification. More information on Wikipedia.

3 Types of weak learners are implemented here: