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This dаtаset cоntаins 3 attributes (Age, incоme, credit_rating), and Lоan_Approval is the target variable. Apply the Naive Bayes classification technique to estimate the class level of the test sample:[Age=41, Income=High, Credit_Rating=Fair] Find all the component probabilities by answering the followings (8 pts): [Tips: you can keep the values in the in the form x/y (such as, 2/3 instead of calculating the actual value)] a. P(Age=41| Yes) = ?b. P (Income = High | Yes) = ? c. P(Credit_Rating=Fair | Yes) = ?d. P(Yes) = ?e. P(Age=41| No) = ?f. P (Income = High | No) = ? g. P(Credit_Rating=Fair | No) = ?h. P(No) = ? Then, find the values of the following (2.5+2.5 = 5 pts): P(Age=41| Yes) * P (Income = High | Yes) * P(Credit_Rating=Fair | Yes) * P(Yes)andP(Age=41| No) * P (Income = High | No) * P(Credit_Rating=Fair | No) * P(No) Then compare which quantity is greater to make the final decision (2 pts).