Lecture 10:
Sasha Rakhlin


Description

We introduce bagging and boosting algorithms. We discuss the bias-variance tradeoff. The gradient descent view of boosting is introduced and a bound on the performance of Adaboost is proved.

Slides

Slides for this lecture: PS,PDF

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