Question: 29. Linear classification Consider the problem of binary classification using the Naive Bayes classifier. You are given two dimensional features (X1, X2) and the categorical

29. Linear classification Consider the problem of binary classification using the

29. Linear classification Consider the problem of binary classification using the Naive Bayes classifier. You are given two dimensional features (X1, X2) and the categorical class conditional distributions in the tables below. The entries in the tables correspond to P(X, = x1(C) and P(X2 = x2]c) respectively. The two classes are equally likely. Class Class C1 C2 C1 C2 X1 = X2 = -1 0.2 0.3 -1 0.4 0.1 0 0.4 0.6 0 0.5 0.3 1 0.4 0.1 1 0.1 0.6 Given a data point, calculate the following posterior probabilities: (25 points) (Writing the calculation procedures) (1) P(C/X;=-1, X=1) (2) P(CzX=-1, X2=1) (3) P(C|Xi=1, X2=-1) (4) P(C2|X1=1, X2=-1) (5) P(C1/X=0, X2=0)

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