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Why is accuracy a poor metric for a dataset that is 99% negative?

A Predicting the majority class always gives 99% accuracy while catching nothing
B Accuracy cannot be calculated on imbalanced data
C Accuracy is always misleading
D It requires balanced classes to compute

Answer

Predicting the majority class always gives 99% accuracy while catching nothing

Precision, recall, F1 and especially PR-AUC are far more informative when the positive class is rare.

All Machine Learning MCQs

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