2. (a) How would you convert a nominal attribute into a numeric one? And why would you possibly want to do so? (b) What is "bagging"? What is "boosting"? And how are they different? (c) What is stacking? (d) What is "stratified 10-fold cross validation"? (e) What is "0.632 bootstrap" and when is it used? (10 Which is a major weakness of the perceptron neural network model? (g) When discretizing a numeric input attribute, we can use "equal frequency binning" or "equal interval binning". What is the difference between the two