Boosting in Machine Learning - Final Formula
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In this lecture we are going to discuss computer vision related approaches such as boosting (adaptive boosting or adaboost) and how to combine weak learners. The basic idea is quite counter-intuitive. If we keep combining several weak learners (for example shallow decision trees) then we can end up with an extremely powerful machine learning algorithm
So this is what we will do. We construct shallow decision trees - that can make binary decisions. Then we combine these weak learners and check the result. Let's get started!
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