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In machine learning, precision-recall curve refers to a plot of precision against recall over decision thresholds, shown to dominate in ROC space exactly when it dominates in PR space. This meaning comes from Davis (2006) in Proceedings of the 23rd international conference on Machine learning - ICML '06.[1]
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