You are given a classifier that attempts to predict whether it will rain tomorrow (+) or not (-). The confusion matrix below gives the results of this classification algorithm on a sample of 1000 consecutive days actual/ predicted 30 20 50 900 i) Compute the accuracy, precision, recall, and F measure for the confusion matrix. Compute precision, recall, and the F-measure with respect to + class only) (ii) Which of these metrics is a poor indicator of the overall performance of your algorithm? Which of these metrics is a good indicator of the overall performance? Give a one sentence reason why this is the case? (iii) Construct a trivial rule-based model which gives better accuracy than the classification algorithm above