Difference between accuracy and f1-score. Where do we use these metrics?

Data Science, AI and ML
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#1

Hypothesis testing

#2

Accuracy is used when the True Positives and True negatives are more important while F1-score is used when the False Negatives and False Positives are crucial. Accuracy can be used when the class distribution is similar while the F1-score is a better metric when there are imbalanced classes.

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