From the results in parts (a), (b), and (c), which method provides a more reliable evaluation of the classifier’s accuracy?
While the .632 bootstrap approach is useful for obtaining a reliable estimate
of model accuracy, it has a known limitation. Consider a two-class problem,
where there are equal number of positive and negative examples in the data.
Suppose the class labels for the examples are generated randomly. The clas-
sifier used is an unpruned decision tree (i.e., a perfect memorizer). Determine
the accuracy of the classifier using each of the following methods.
From the results in parts (a), (b), and (c), which method provides a
more reliable evaluation of the classifier’s accuracy?
Answer:
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