Which option gives the correct values for accuracy and precision from the confusion matrix?

The correct answer is B. Accuracy = 80%, Precision = 75%. From the confusion matrix: True Positives (TP) = 15 False Positives (FP) = 5 False Negatives (FN) = 15 True Negatives (TN) = 65 Accuracy= (TP + TN) / Total = (15 + 65) / 100 Precision= TP / (TP + FP) Section3.2 - Functional Performance Criteriain the syllabus explains accuracy…

Machine Learning (ML)

Question

Options

AAccuracy = 50%, Precision = 75%
BAccuracy = 80%, Precision = 75%
CAccuracy = 75%, Precision = 80%
DAccuracy = 80%, Precision = 50%

How the community answered

(19 responses)

A
11% (2)
B
79% (15)
C
5% (1)
D
5% (1)

Explanation

From the confusion matrix: True Positives (TP) = 15 False Positives (FP) = 5 False Negatives (FN) = 15 True Negatives (TN) = 65 Accuracy= (TP + TN) / Total = (15 + 65) / 100 Precision= TP / (TP + FP) Section3.2 - Functional Performance Criteriain the syllabus explains accuracy and precision exactly these ways when evaluating ML classification performance. Option B is therefore the only correct pair of values.

Topics

#confusion matrix#accuracy#precision#performance metrics

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