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Consider the data with categorical predictor x1 = {green or red} and numerical predictor x2 and the class variable y shown in the following table. The weights for a round of boosting are also shown in the table. Suppose the classifier built from this round of boosting assigns y = 1 for x2 < 0.45 and y = -1 for x2 > 0.45. Compute the coefficient α for this classifier in the adaboost algorithm.
Q. Explain working of DotMatrix or InkJet Printers? Three major issues consider the quality of characters generated by DotMatrix/InkJet Printers: - Number of dots in the matrix
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1. Insert the following characters with their respective priorities (shown as ordered pairs) into an empty treap: (K, 17), (F, 22), (P, 29), (M, 10), (N, 15), (L, 26), (G, 13),
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