According to this article (which references the original paper), this is the SAMME algorithm for multiclass classification using Adaboost:

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I would like to understand what is this term in step 2.d which multiplies the $\alpha^{(m)}.$ It also appears in step 2.b. I think it has something to do with the samples that are missclassified, but i can't understand what it does exactly.

Also, i would appreciate some explanation about the Output (prediction) of this algorithm.



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