Model Precision
Percentage
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.
Formula
(True Positives / (True Positives + False Positives))
Example
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%.