Let us say the cost of a False Positive is 10 units and the…
Let us say the cost of a False Positive is 10 units and the cost of a False negative is 2 units. In this context answer the following. (a) (6) How would you adjust the decision tree algorithm so that its performance on unseen cases minimizes the total expected cost instead of maximizing the accuracy? (b) (6) Recall the Support Vector Machine formulation discussed in class, specifically the case in which we minimize the cost of misclassifications using a constant parameter C. Suggest a solution for learning an SVM classifier in which the cost of the two types of errors are different. Do not write any formulas, describe your ideas in language.