F1 Score vs Accuracy

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You are building a fraud detection model where only 1% of transactions are fraudulent. A model that predicts 'not fraud' for everything achieves 99% accuracy. Which metric better captures model quality for this task?

Multiple Choice

Accuracy, since 99% is very high F1 score, since it accounts for both precision and recall on the minority class Mean Squared Error, since it penalizes large errors R-squared, since it measures explained variance

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F1 Score vs Accuracy

Multiple Choice

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