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(a) Misclassification error = 1 - Accuracy (b) True Positive Rate (TPR) = Recall = Sensitivity = TP / (TP + FN) (c) False Positive Rate(FPR) = 1- Specificity = 1 - (TN / (TN + FP)) %3D %3D

(a) Misclassification error = 1 - Accuracy (b) True Positive Rate (TPR) = Recall = Sensitivity = TP / (TP + FN) (c) False Positive Rate(FPR) = 1- Specificity = 1 - (TN / (TN + FP)) %3D %3D

A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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2. Read explanation of the confusion matrix and corresponding evaluation criterions in classification in the following link: https://en.wikipedia.org/viki/Confusion_ matrix. Use the following confusion matrix from a cancer classification problem to compute the following measurements. (a) Misclassification error = 1 - Accuracy (b) True Positive Rate (TPR) = Recall = Sensitivity = TP / (TP + FN) (c) False Positive Rate(FPR) =1- Specificity =1 - (TN / (TN + FP)) (d) Precision = TP / (TP + FP) (e) Fi score = 2 * Precision Recall Precision+Recall Actual Target \ Predicted Target Predicted Cancer = Yes Predicted Cancer No Total Actual Cancer = Yes 90 210 300 Actual Cancer No 140 9560 9700 Total 230 9770 10000
Transcribed Image Text:2. Read explanation of the confusion matrix and corresponding evaluation criterions in classification in the following link: https://en.wikipedia.org/viki/Confusion_ matrix. Use the following confusion matrix from a cancer classification problem to compute the following measurements. (a) Misclassification error = 1 - Accuracy (b) True Positive Rate (TPR) = Recall = Sensitivity = TP / (TP + FN) (c) False Positive Rate(FPR) =1- Specificity =1 - (TN / (TN + FP)) (d) Precision = TP / (TP + FP) (e) Fi score = 2 * Precision Recall Precision+Recall Actual Target \ Predicted Target Predicted Cancer = Yes Predicted Cancer No Total Actual Cancer = Yes 90 210 300 Actual Cancer No 140 9560 9700 Total 230 9770 10000
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