PRC stands for precision–recall curve. It is a method of visualizing the tradeoff between precision and recall. Precision and recall are both model performance metrics , aka cost function, for classification systems.


In statistics and machine learning, precision is a measure of how often the positives identified by a learning model are true positives. This is a division of true positives (based on the confusion matrix) by all estimated positives (=true positives + false positives). The precision metric is commonly used in conjunction with recall, to evaluate ... Read more