Ghost and Skip Instructions:Number of questions: 13Time limit: 7 minutesMust be finished in one sitting. You cannot save and finish later.Questions displayed per page: 1Will allow you to go back and change your answers.Will not let you finish with any questions unattempted. 1 / 13 If the recall is 80% and the precision is 75%, what is the True Positive Rate? 25% 75% 20% 80% 2 / 13 Calculate Precision (true positives) / (true positives - false positives) (true positives) / (true positives + false positives) (false positives) / (true positives + false positives) (true positives + false positives) 3 / 13 Precision is a .. Positive predictive value Average predictive value Positive-negative predictive value Negative predictive value 4 / 13 If the recall is 80% and the precision is 75%, what is the False Positive Rate? 25% 20% The FPR cannot be found from the information given. 5% 5 / 13 If you always predict false positive your classifier will have a recall of None of the above 100% 0% Not possible 6 / 13 We are interested in reducing the number of false negatives. Which of the following metrics should we primarily look at? Accuracy Precision Recall Average 7 / 13 True positive rate (TPR) is Fraction of actually positive case Precision of given positive case Average of given positive case All are true 8 / 13 Recall is a Total amount Average of the total amount Product of the total amount Fraction of the total amount 9 / 13 A __________ is the incorrect identification of data classifying as “normal” data which is in fact abnormal. False Negative True Negative False Positive True positive 10 / 13 What would a recall of 80% mean? Positive cases were found by the detector Positive False cases were found by the detector None of the above Negative true cases were found by the detector 11 / 13 Calculate Recall (false positives) / (true positives + false negatives) (true positives) / (true positives + false negatives) (true positives - false negatives) (true positives) / (true positives + true negatives) 12 / 13 True positive is also termed as Summation of negative case Recall Summation of positive case Precision 13 / 13 If you always predict true positive, your classifier will have a recall of 0% 100% Not possible None of the above Your score is LinkedIn Facebook Twitter 0% Restart quiz
