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Question 1. Classification: decide to do K-Nearest-Neighbor Given Given (x, classification. (xi, yi) for i y) for i.i.d. ~ i = 1,..., n where

Question 1. Classification: decide to do K-Nearest-Neighbor Given Given (x, classification. (xi, yi) for i y) for i.i.d. ~ i = 1,..., n where y, is binary label, we (a) How would you choose K such that kNN a consistent classifier? Namely, what is the choice of K such that the mis-classification error can decrease to 0 as n o? (b) Suppose (x, y) Fxy = FxFy, i.e., x and y are independent. As n , what value shall the mis-classification error converge to?

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