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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the concept of boosting, focusing on the Adaboost algorithm and forward stagewise additive modeling. It explains the derivation of Adaboost as FSAM on the exponential loss, boosted trees, and interpretations of Adaboost. The lecture also discusses the solutions for B and G, comparing with Adaboost, boosting of trees, and general gradient tree boosting for classification.