Answer to Question #345906 in Statistics and Probability for Toilet Gamer

Question

Q: Given Email B with its feature vector. Compute the probability of email B being “spam” and “ham” using Naïve bayes algorithm and then finally assign class label (spam or ham).

                                        P(spam) = 0.65

  Email B = < 0, 1, 1, 1 >, = < count(meeting), count(enron), count(dating), count(hi) >

       P (meeting | spam) = 0.6,                          P (meeting | ham) = 0.02

       P (enron | spam) = 0.4,                              P (enron | ham) = 0.001

       P (dating | spam) = 0.7,                             P (dating | ham) = 0.005

        P (hi | spam) = 0.3,                                   P (hi | ham) = 0.09

Answer 1

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