Precision-Recall Space
(Redirected from PR space)
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A Precision-Recall Space is a metric space for a Prediction-Recall function.
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- Counter-Example(s):
- See: Precision-Recall Curve, Unit Space, True Positive Rate, Precision Rate.
References
2006
- (Davis & Goadrich, 2006) ⇒ Jesse Davis, and Mark Goadrich. (2006). “The Relationship Between Precision-Recall and ROC Curves.” In: Proceedings of the 23rd International Conference on Machine learning. ISBN:1-59593-383-2 doi:10.1145/1143844.1143874
- QUOTE: Receiver Operator Characteristic (ROC) curves are commonly used to present results for binary decision problems in machine learning. However, when dealing with highly skewed datasets, Precision-Recall (PR) curves give a more informative picture of an algorithm's performance. We show that a deep connection exists between ROC space and PR space, such that a curve dominates in ROC space if and only if it dominates in PR space.