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Question 53 - DSA-C02 discussion

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Which of the following is a common evaluation metric for binary classification?

A.
Accuracy
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A.
Accuracy
B.
F1 score
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B.
F1 score
C.
Mean squared error (MSE)
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C.
Mean squared error (MSE)
D.
Area under the ROC curve (AUC)
Answers
D.
Area under the ROC curve (AUC)
Suggested answer: D

Explanation:

The area under the ROC curve (AUC) is a common evaluation metric for binary classification, which measures the performance of a classifier at different threshold values for the predicted probabilities. Other common metrics include accuracy, precision, recall, and F1 score, which are based on the confusion matrix of true positives, false positives, true negatives, and false negatives.

asked 23/09/2024
Dimitri Bennett
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