In a naive Bayes problem let, P(PW) - probability of positive sentiment = 0.5 P(NW) probability of negative sentiment = 0.5 Also, the following conditional probabilities are known. P(you| PW) 0.18 P(you| NW) 0.3 P(good| PW) 0.23 P(good| NW) 0.54 P(are| PW) 0.47 P(are| NW) 0.04 P(person | PW) 0.12 P(person | NW) 0.12 Identify whether the following message would be classified as positive or negative using the above values. Show the details of your conclusion. Message: good person

Suppose one or more words in the test data is not present in the training data. Considering the nave Bayes model, Can you classify the test data? Discuss at least one method to handle this situation.