What is the trade-off between precision and recall? — A model that predicts “yes” when it’s even a little bit confident will probably have a high recall but a low precision; a model that predicts “yes” only when it’s extremely confident is likely to have a low recall and a high precision. Alternatively, you can think of this as a trade-off between false positives and false negatives. Saying “yes” too often (high recall) will give you lots of false positives; saying “no” too often will give you lots of false negatives (high precision).