Calculate the probabilities that would be required by a Naive Bayes Classifier trained on the dataset in Table?

3. QUESTION 3 (TOTAL MARKS 30) The dataset in Table 3 shows a small set of five historical emails. The features included are IMAGES (represents how many images the email contains, possible values are: none, one, few), KNOWN SENDER (represents if the sender email is in the address book, possible values: yes, no) and B WORDS (represents if the email contains blacklisted words, possible values: none, one, few). The target feature SPAM that shows if that instance was a spam or not (possible values: yes, no). ID IMAGES KNOWN SENDER BWORDS no none few SPAM yes yes no none few few yes yes no none none no 4 5 one few no one no Table 3: Dataset for Question 3. (a) Calculate the probabilities that would be required by a Nave Bayes classifier trained on the dataset in Table 3. (15 marks)