Refer to the scenario described in Problem 10 and the file BlueOrRed. Partition the data into training
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#records in a terminal node to 1. In Step 3 of XLMiner's Classification Tree procedure, set the maximum number of levels to seven. Generate the Full tree, Best pruned tree, and
Minimum error tree. Generate lift charts for both the validation data and the test data.
a. Interpret the set of rules implied by the best pruned tree that characterize undecided voters.
b. In the CT_Output1 sheet, why is the overall error rate of the full tree 0 percent? Explain why this is not necessarily an indication that the full tree should be used to classify future observations and the role of the best pruned tree.
c. For the default cutoff value of 0.5, what is the overall error rate, Class 1 error rate, and Class 0 error rate of the best pruned tree on the test data?
d. Examine the decile-wise lift chart for the best pruned tree on the test data. What is the first decile lift? Interpret this value.
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Related Book For
Essentials of Business Analytics
ISBN: 978-1285187273
1st edition
Authors: Jeffrey Camm, James Cochran, Michael Fry, Jeffrey Ohlmann, David Anderson, Dennis Sweeney, Thomas Williams
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