You are working on a text classification problem using a Naive Bayes classifier to determine whether an email is "Spam" or "Not Spam" . You have trained your model using a dataset of 1000 emails, with 600 of them labeled as "Spam" and 400 labeled as "Not Spam." You've collected statistics on the occurrence of two words, "Won" and "Money" in these emails: | Keyword | label of email | Probability | |---|---|---| | Won | Spam | P(\text{Won} \Vert Spam) = 0.45 | | Won | Not Spam | P(\text{Won} \Vert NotSpam) = 0.05 | | Money | Spam | P(\text{Money} \Vert Spam) = 0.3 | | Money | Not Spam | P(\text{Money} \Vert NotSpam) = 0.02 | You receive a new email containing both the "Won" and "Money" keywords and want to classify it using Naive Bayes. Use the Naive Bayes formula to calculate the probability that the new email is classified as "Spam." Hint: Assume that these are only two possible words (that is there are only two features)

Machine Learning Techniques · End Term · 3 Sept 2023 · May 2023 term · Set QPD1-S1

Question 3: You are working on a text classification problem using a …

Question 3

+6 marksNumerical answer

You are working on a text classification problem using a Naive Bayes classifier to determine whether an email is "Spam" or "Not Spam" . You have trained your model using a dataset of 1000 emails, with 600 of them labeled as "Spam" and 400 labeled as "Not Spam." You've collected statistics on the occurrence of two words, "Won" and "Money" in these emails:

Keyword	label of email	Probability
Won	Spam	$P(\text{Won} \Vert Spam) = 0.45$
Won	Not Spam	$P(\text{Won} \Vert NotSpam) = 0.05$
Money	Spam	$P(\text{Money} \Vert Spam) = 0.3$
Money	Not Spam	$P(\text{Money} \Vert NotSpam) = 0.02$

You receive a new email containing both the "Won" and "Money" keywords and want to classify it using Naive Bayes.

Use the Naive Bayes formula to calculate the probability that the new email is classified as "Spam."

Hint: Assume that these are only two possible words (that is there are only two features)

Show answer

Correct answer: 0.99 (accepted within ±0.01)

See the whole paper Take it as a mock test

Question 3 of 17 in the IIT Madras BS Machine Learning Techniques (MLT) End Term paper sat on 3 Sept 2023, in the May 2023 term (IIT M DIPLOMA ET1 EXAM QPD1 S2 03 Sep). It carries 6 marks.

Question 3: You are working on a text classification problem using a …

Question 3

More questions from this paper