18. Consider the task of building a classifier from random data, where the attribute values are generated randomly irrespective of the class labels. Assume the data set contains instances from two classes, + and ." Half of the data set is used for training while the remaining half is used for testing. a. Suppose there are an equal number of positive and nega- tive instances in the data and the decision tree classifier predicts every test instance to be positive. What is the ex- pected error rate of the classifier on the test data? b. Repeat the previous analysis assuming that the classifier predicts each test instance to be positive class with proba- bility 0.8 and negative class with probability 0.2