Evaluate precision and recall results 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?
This looks like it could be a homework problem, so consider updating it with the homework tag if so.

The second model has the same precision, but worse recall, than model 1. Therefore we would rather have model 1 than model 2.

The third model has worse recall than model 1, and worse precision than model 1, therefore we would rather have model 1 than model 3.

Thus, model 1 is the best object detection model.