The following table shows the precision and recall values I obtained for three object detection models.
I evaluate the first two models as the following. The target is to find the best object detection model for that particular data set.
Model 1 has a high recall and precision values. High precision relates to a low false-positive rate, and high recall relates to a low false-negative rate. High scores for both show that the model is returning accurate results. Model 2 has high precision but low recall. This means it returns very few results, but most of its identified objects are correct.
How can I evaluate the third one?