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Suppose a categorical response Y can take on 1, 2, or 3. We have two categorical predictors X1 and X2. X1 has two levels, denoted by “A” and “B”. X2 has three levels, denoted by “a”, “b”, and “c”. A training data set consists of 50 observations as follow: Y = 3 Y = 1 X2 a b Y = 2 X2 a b c A 2 1 6 X2 a b c с A 3 1 1 A 2 4 2 X X Xi B 1 1 3 B 1 8 2 B 9 1 2 = a. For instance, there are 3 observations having Y = 1, X1 = A, and X2 (a) Construct the Bayes classifier table for û and the posterior probability estimate P(Y = j|X1, X2). (b) Construct the naive Bayes classifier table for Ỹ and the posterior probability estimate PY =jX1, X2) =
Suppose a categorical response Y can take on 1, 2, or 3. We have two categorical predictors X1 and X2. X1 has two levels
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Suppose a categorical response Y can take on 1, 2, or 3. We have two categorical predictors X1 and X2. X1 has two levels
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