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Deriving the training error for AdaBoost: In class, we discussed the steps of the AdaBoost algorithm. Recall that the final hypothesis for a Boolean classification problem at the end of T iterations is given by:H(x) = sign(αht(x))The above equation states that the final hypothesis is the weighted hypothesis generated at the end of each individual step. Also, recall that the weight for the point at step t 1 is given by:Dt 1(i) = Dt(i) * e^(-αht(y(i)) * Ztwhere:- Dt(i) is the normalized weight o
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