The following confusion matrix represents the functional performance of a classifier. Which ONE of the following is the correct calculation for the accuracy of the classifier?

The correct answer is D. (60 + 11) / (60 + 11 + 20 + 9) * 100% = 71%. Accuracy = (True Positives + True Negatives) / (Total Samples) - True Positives (TP) = 60 - True Negatives (TN) = 11 - False Positives (FP) = 20 - False Negatives (FN) = 9 Accuracy = (60 + 11) / (60 + 11 + 20 + 9) * 100% = 71%

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Question

Options

A60 / (60 + 20) * 100% = 75%
B60 / (60 + 9) * 100% = 87%
C2 * (60 / (60 + 20) * 60 / (60 + 9)) / (60 / (60 + 20) + 60 / (60 + 9)) * 100% = 80%
D(60 + 11) / (60 + 11 + 20 + 9) * 100% = 71%

How the community answered

(24 responses)

A
17% (4)
B
4% (1)
C
4% (1)
D
75% (18)

Explanation

Accuracy = (True Positives + True Negatives) / (Total Samples) - True Positives (TP) = 60 - True Negatives (TN) = 11 - False Positives (FP) = 20 - False Negatives (FN) = 9 Accuracy = (60 + 11) / (60 + 11 + 20 + 9) * 100% = 71%

Topics

#confusion matrix#accuracy calculation#classifier performance#functional performance

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