Question: Problem 1) [Paper-based] Assume that a classification model is trained to detect fraudulence emails from non-fraudulence ones, and we would like to test the classifier's

Problem 1) [Paper-based] Assume that a classification model is trained to detect fraudulence emails from non-fraudulence ones, and we would like to test

Problem 1) [Paper-based] Assume that a classification model is trained to detect fraudulence emails from non-fraudulence ones, and we would like to test the classifier's efficacy in making such detections. A test data containing 40 email instances are provided. The test data labels are given and denoted as gold-standard labels. The table below provides the gold-standard and predicted labels using this classifier for each data sample. "0" means non-fraudulence emails, and "1" indicates fraudulence emails. Using this table, answer the following questions. a) Calculate and show the confusion matrix. NOTE: Detecting fraudulent emails 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 Measure of the model. f) Calculate the recall and precision

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