need help with all parts! will give a thumbs up!

Problem 1) [Paper-based] Assume that a classificanion model is trained to detect fracdulenee emails from non-fraudulence ones, and we would hike to test the classifier's dfficacy in making such detections. A test data containing 40 email instances are provided. The teet data labels are given and denoted as gold-standard labels. The takic below provides the gold-atandard and prediced labels using this classifier for each data sample, "or mexns men-traadulence emails, and " 1 " indicates fraudulence emails. Using this table, answer the following questions. 1 a) Calculate and shaw the confusion matrix. NOTE: Detecting fradulent enuils is "important". b) Calculate and provide the accuracy of the model. c) Calculate the sensitivity of the model. d) Calculate the specificity of the model. e) Calculate the F1 Measire of the model. f) Calculate the recall and precision