Question: We have a classification problem with Nclasses. Let us say we know that a true Bayes classifier for this problem has an error rate of

We have a classification problem with Nclasses. Let us say we know that a true Bayes classifier for this problem has an error rate of

0.15 .

Let us say build a decision tree using a training set of size

1000

to handle this problem, what is the lowest error rate you could possibly achieve. Can you improve this error rate by using more training samples? Justify your answer.

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