Question: 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
Suppose the class labels for the examples are generated randomly. The classifier used is an un-pruned decision tree (i.e., a perfect memorizer). Determine the accuracy of the classifier using each of the following methods.
(a) The holdout method, where two-thirds of the data are used for training and the remaining one-third are used for testing.
(b) Ten-fold cross-validation.
(c) The .632 bootstrap method.
(d) From the results in parts (a), (b), and (c), which method provides a more reliable evaluation of the classifier's accuracy?
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