1. Software Engineering
  2. Artificial Intelligence

Model Precision


Model Precision measures the accuracy of positive predictions made by an AI model. It’s crucial for scenarios where false positives have significant consequences. High precision indicates a lower rate of false positives.


(True Positives / (True Positives + False Positives))


If an AI model identifies 80 relevant items (true positives) out of 100 total identified items, where 20 are irrelevant (false positives), precision is (80/(80+20)) = 80%.