3. Answer the following questions about supervised learning: (b) What is the purpose of k-fold cross-validation? How is it done? (c) Explain the concept of boosting when learning an ensemble based...

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Extracted text: 3. Answer the following questions about supervised learning: (b) What is the purpose of k-fold cross-validation? How is it done? (c) Explain the concept of boosting when learning an ensemble based classifier. (d) How is a naïve Bayesian model different from a regular one? What is the motivation (or advantage) of using a naïve model?