Answer Happy

Please answer each of the following questions: a) What is precision? What is recall?What is the accuracy of a classification model? What are false positives? What are false negatives? b) When we applied a Naïve Bayes classification model to the bank testing data set, the performance (classification) operator generates the following contingency table. Based on the contingency table, please find and calculate the relevant performance measures and fill out your answers in the following table. true Yes true NO Classification precision Pred. YES 156 43 Pred. NO 42 179 Class recall Fill out the following table based on the above contingency table: Total number examples 420 Accuracy Number of true positives Number of false positives Number of false negatives Number of true negatives Recall (true YES) Precision (Pred. YES)