Page 9 of 11 c Consider the following confusion matrix tables The four tables

Page 9 of 11 c consider the following confusion

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(c) Consider the following confusion matrix tables. The four tables 4A, 4B, 4C, and 4D summarise the predicted and actual number of students in each category when using the trees in Figures 4.1 and 4.2 on test and training data respectively. Actual Table 4A Predicted admit border notadmit admit 15 0 0 border 0 14 0 notadmit 0 0 13 Actual Table 4B Predicted admit border notadmit admit 7 7 2 border 3 4 4 notadmit 5 3 7 Actual Table 4C Predicted admit border notadmit admit 11 4 0 border 0 14 0 notadmit 0 2 11 Actual Table 4D Predicted admit border notadmit admit 5 10 1 border 1 6 4 notadmit 5 4 6 (i) For each table 4A, 4B, 4C and 4D, what is the error rate? (ii) Which two tables do you believe relate to the test data? Explain your answer. Page 10 of 11
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Question 5 [6 + 6 + 3 = 15 marks] An online provider of statistics courses is interested in assessing alternative sequencing and combinations of courses, and therefore wishes to conduct association analysis on its data for past students. Table 5.1 shows a sample of their data, with each row representing an individual student and each column representing a statistics course that they offer as identified by the column headings. Table 5.1 ID Intro Expt design StatWrite Survey DataMining Cat Data Regression Forecast 1 1 0 0 0 1 0 0 0 2 0 1 0 1 0 1 0 0 3 0 1 1 1 1 1 1 0 4 1 0 0 0 0 0 0 0 5 1 0 0 0 1 0 0 0 6 0 0 0 0 1 0 1 1 7 1 0 0 0 0 0 0 0 8 0 1 1 0 0 1 0 1 9 1 0 0 0 0 0 0 0 10 0 0 0 0 0 1 1 0 11 1 0 0 0 0 0 0 0 12 0 0 0 0 1 0 0 0 13 0 0 0 0 1 0 0 0 14 0 0 0 1 1 0 0 1 15 0 0 0 1 1 0 1 1 16 1 1 1 1 0 1 0 1 17 1 0 0 0 0 0 1 0 18 1 0 0 0 0 0 0 1 19 1 0 0 0 0 0 0 0 20 0 0 0 0 0 0 1 0 21 0 0 1 1 0 1 0 0 22 0 0 0 0 1 0 1 1 23 1 0 1 1 0 1 0 0 24 1 0 0 0 0 0 1 1 25 1 0 1 0 0 0 0 0 26 0 1 1 0 1 0 1 1 27 0 1 1 0 1 1 1 0 28 1 0 0 0 1 0 1 1 Consider the association rule {Forecast, Regression} {DataMining}. (a) Based on the sample provided in Table 5.1, calculate for this association rule The support of the antecedent itemset The confidence of the association rule The lift of the association rule. (b) Interpret each of the numbers calculated in (a) in relation to the present application, and explain any role they may have in assessing the usefulness of the association rule. (c) If you find out that a student has taken the Forecast and Regression courses, does this make it more likely that they will take the DataMining course? If so, how much more likely? Page 11 of 11
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