The following table summarizes a data set with three attributes A, B, C and two class labels
Question:
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(a) According to the classification error rate, which attribute would be chosen as the first splitting attribute? For each attribute, show the contingency table and the gains in classification error rate.
(b) Repeat for the two children of the root node.
(c) How many instances are misclassified by the resulting decision tree?
(d) Repeat parts (a), (b), and (c) using C as the splitting attribute.
(e) Use the results in parts (c) and (d) to conclude about the greedy nature of the decision tree induction algorithm.
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a The error rate for the data without partitioning on any attribute is After splitting on attribute ...View the full answer
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Related Book For 
Introduction to Data Mining
ISBN: 978-0321321367
1st edition
Authors: Pang Ning Tan, Michael Steinbach, Vipin Kumar
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