Part 2. Naive Bayes (Han 8.3 & Witten 4.2) Consider the following training data from the AllElectronics Customer Database (table 8.1 Han 338), which tracks whether a customer buys a computer or not (the class label), based on other important demographic data (i.e., attributes such as age, income, student (yes or no), and credit rating). This data can be used to training a classifier (Bayes, ID3, etc.) which will predict the likelihood of a new customer buying a computer based on his/her demographic data. AllElectronics Customer Database RIP Age Income Student CreditRating buyCompuer 1 Youth High No fair No 2 Youth High No Excellent No 3 middleAged High No fair Yes 4 Senior Medium No fair Yes Senior Low Yes fair Yes 6 Senior Low Yes Excellent No 7 middleAged Low Yes Excellent Yes 8 Youth Medium No fair No 9 Youth Low Yes fair Yes 10 Senior Medium Yes fair Yes 11 Youth Medium Yes Excellent Yes 12 middleAged Medium No Excellent Yes 13 middleAged High Yes fair Yes 14 Senior Medium No Excellent No 1. Use basic Naive Bayes method to determine the whether a new customer would buy a computer, given the following demographic data: (20 points) New customer Age Income Student CreditRating butComputer Senior Low No Excellent