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SOLVED: Please answer with detailed explanation. If can't explain please try at most to provide an explanationQ.2 Naive Bayesian Classification (25 points)The following dataset contains loan information and can be used to try to predict whether a borrower will default (the last column is the classification). Use the naive Bayesian method to determine whether a loan X = (Home Owner = No, Marital Status = Married, Income = High) should be classified as a Defaulted Borrower or not.Home OwnerMarital

SOLVED: Please answer with detailed explanation. If can't explain please try at most to provide an explanationQ.2 Naive Bayesian Classification (25 points)The following dataset

VIDEO ANSWER: The standard deviation of all of our p-hats is going to be 0.11 times 0.89, and the average of all of our p-hats is going to be 9%. The square ro…

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SOLVED: For the 14 data points in Table 3.2, draw the naive Bayes classifier. Find all its CPTs. Compute the predicted target attribute for the example appearing below the line under D14. Compute the conditional probability that this is correct given the observed data.Day Outlook Temperature Humidity Wind PlayTennis D1 Sunny Hot High Weak No D2 Sunny Hot High Strong No D3 Overcast Hot High Weak Yes D4 Rain Mild High Weak Yes D5 Rain Cool Normal Weak Yes D6 Rain Cool Normal Strong No D7 Overcast

SOLVED: For the 14 data points in Table 3.2, draw the naive Bayes classifier. Find all its CPTs. Compute the predicted target attribute for the example appearing below the line under D14. Compute the conditional probability that this is correct given the observed data.Day Outlook Temperature Humidity Wind PlayTennis D1 Sunny Hot High Weak No D2 Sunny Hot High Strong No D3 Overcast Hot High Weak Yes D4 Rain Mild High Weak Yes D5 Rain Cool Normal Weak Yes D6 Rain Cool Normal Strong No D7 Overcast