MIT 6.034 Artificial Intelligence, Fall 2010
View the complete course: http://ocw.mit.edu/6-034F10
Instructor: Patrick Winston
Can multiple weak classifiers be used to make a strong one? We examine the boosting algorithm, which adjusts the weight of each classifier, and work through the math. We end with how boosting doesn't seem to overfit, and mention some applications.
License: Creative Commons BY-NC-SA
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Tagged under: machine learning,boosting,strong classifier,weak classifier,error rate,training,weights,distribution,decision tree,stump,binary classification
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