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I read somewhere that Gradiant boosting is a generalization of Adaboost. However, I cannot see why. Can Anyone elaborate?

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    $\begingroup$ AdaBoost can be formulated as gradient boosting with exponential loss. Have a look at chapter 10 of The Elements of Statistical Learning: web.stanford.edu/~hastie/ElemStatLearn $\endgroup$
    – sebp
    Commented Aug 15, 2018 at 19:48
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    $\begingroup$ There's some subtleties to this question. It could be interpreted in a few ways. 1) Is AdaBoost (mathematically) a special case of Gradient Boosting? (yes). 2) Was gradient boosting discovered as a way to use the AdaBoost model in more general situations (sort of). 3) Is it best to view Gradient Boosting as a generalization of AdaBoost in 2018 (No, it better to think of Gradient Boosting as a primary concept, and AdaBoost as secondary). Which was your intention (or something else entirely...)? $\endgroup$ Commented Aug 15, 2018 at 21:44
  • $\begingroup$ My main question is about '1' . If Adaboost is a generalization of Gradiant Boosting and also if using Gradiant Boosting with the right error distribution will yield the same result as adaboost. However, I am not sure what you exactly mean in number '3'. Can you explain a bit? $\endgroup$
    – ABIM
    Commented Aug 16, 2018 at 12:47

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