1. Use Nave Bayes classification method (and the Bayes classification rule) to classify the following two feature vectors:

a. [X1 =1,X2 =1,X3 =0]

b. [X1 =0,X2 =1,X3 =0]

Table 1 gives the training data to estimate probabilities. The class labels are 0 or 1. Use 3 as the m-value i.e. m = 3 and use prior probability as 0.5 i.e., p = 0.5

Table 1. Labeled training data.

X1 X2 X3 000 001 011 100 101 111

Class Label

0 1 0 1 0 0

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2. Use Tree Augmented Nave Bayes (and the Bayes classification rule) to classify the two feature vectors. (Dont use m-estimate for the probabilities