Boosting - is a machine learning meta-algorithm for performing supervised learning. Boosting is based on the question posed by Kearns[1]: can a set of weak learners create a single strong learner? A weak learner is defined to be a classifier which is only slightly correlated with the true classification. In contrast, a strong learner is a classifier that is arbitrarily well correlated with the true classification.
Monday, May 11, 2009
boosting
Boosting - is a machine learning meta-algorithm for performing supervised learning. Boosting is based on the question posed by Kearns[1]: can a set of weak learners create a single strong learner? A weak learner is defined to be a classifier which is only slightly correlated with the true classification. In contrast, a strong learner is a classifier that is arbitrarily well correlated with the true classification.
