What is a precision-recall curve?
A curve of precision versus recall at different classification thresholds.
precision-recall curve explained in plain English
A curve of precision versus recall at different classification thresholds.
Example
Practitioners refer to precision-recall curve when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
People also read
- A/B testing
A statistical way of comparing two (or more) techniques—the A and the B.
- ablation
A technique for evaluating the importance of a feature or component by temporarily removing it from a model.
- accuracy
The number of correct classification predictions divided by the total number of predictions.
- activation function
A function that enables neural networks to learn nonlinear (complex) relationships between features and the label.
- active learning
A training approach in which the algorithm chooses some of the data it learns from.
- adaptation
Synonym for tuning or fine-tuning.
- agglomerative clustering
See hierarchical clustering.
- anomaly detection
The process of identifying outliers.
- area under the PR curve
See PR AUC (Area under the PR Curve).
- area under the ROC curve
See AUC (Area under the ROC curve).