Repeat part (a) using X as the first splitting attribute and then choose the best remaining attribute for splitting at each of the two successor nodes. What is the error rate of the induced tree?

Consider the following set of training examples.


After choosing attribute X to be the first splitting attribute, the sub-


sequent test condition may involve either attribute Y or attribute Z.


For X = 0, the corresponding counts for attributes Y and Z are shown


in the table below.





The error rate using attributes Y and Z are 10/120 and 30/120, re-


spectively. Since attribute Y leads to a smaller error rate, it provides a





better split.


For X = 1, the corresponding counts for attributes Y and Z are shown


in the tables below.





The error rate using attributes Y and Z are 10/80 and 30/80, respec-


tively. Since attribute Y leads to a smaller error rate, it provides a





better split.


The corresponding two-level decision tree is shown below.


![10074|320x119](uplo

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