[9_3_B]
Please answer this question step by step
Extracted text: Answer the following questions about supervised learning: What is the difference between parametric and non-parametric models? Also give an example 3. (а) each. (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?
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