שאלה | How does PASS@K differ from traditional accuracy metrics?

How does PASS@K differ from traditional accuracy metrics?

		PASS@K considers a prediction as correct if the correct answer is within the top K predictions, whereas traditional accuracy metrics consider a prediction as correct only if it exactly matches the ground truth
		PASS@K and traditional accuracy metrics are synonymous and represent the same evaluation measure
		PASS@K evaluates the model's performance based on the ratio of true positives to false positives, while traditional accuracy metrics focus on overall correctness
		PASS@K evaluates the model's performance based on the ratio of true positives to true negatives, while traditional accuracy metrics focus on precision and recall