Question 7 (a) Choosing appropriate classifiers Y For the dataset in Figure above, among k-NN, Decision Trees, and Nave Bayes, which classifier would have the worst performance? Provide a brief explanation justifying your choice. (b) If the training set is such that every combination of attribute values is present in the training data and each combination is either labeled positive or negative, which of the following classification techniques can be used to learn a model with perfect classification (zero errors) on the training set? Briefly explain your answer. a. Decision Trees b. Nave Bayes c. KNN