D. $88K OE $89K QUESTION 14 (14.3) The confusion matrix below shows results from a data mining model. The model attempts to predict whether a customer will buy a product. As a percentage of the total number of results, how often did the model make a mistake? Write your answer rounded to one decimal place in the space below. DO NOT INCLUDE THE PERCENTAGE SIGN IN YOUR ANSWER. Predicted 'Yes' Predicted 'No' Actual 'Yes' 500 125 Actual 'No' 75 $50 QUESTION 15 (15.1) The confusion matri glow shows results from a data mining model. The model attempts to predict whether a customer will buy a product. As a percentage, what is the precision of the model? Write your answer rounded to one decimal place in the space below. DO NOT INCLUDE THE PERCENTAGE SIGN IN YOUR ANSWER. Predicted 'Yes' Predicted 'No' Actual 'Yes' 507 143 Actual 'No' 169 581 QUESTION 16 (16.2) What is the practical significance of higher precision in a data mining model? A The ratio of correctly predicted positive outcomes to the total number of predicted positive outcomes. B. The model is more sensitive for positive outcomes, l.e., better able to identify them. O C Users can have more confidence that the model is correct when it predicts a positive outcome. O D. The model is more 'sensitive' for negative outcomes, l.e., better able to identify them. O E. Users can have more confidence that the model is correct when it predicts a negative outcome. QUESTION 17 (17 4) The data below show six baskets of items that were bought together at a grocery store. 1 Hotdogs, Buns, Ketchup 4 Chips, Buns, Coke 2 Buns, Coke 5 Chips, Ketchup 3 Hotdogs, Coke, Chips 6 Hotdogs, Chips, Ketchup What level of Support do we have for the association rule Chips . Buns? Write your answer in the space below, Round to the nearest whole percentage point but DO NOT INCLUDE THE PERCENTAGE SIGN IN YOUR