Introduction
You usually can't have both perfect precision and perfect recall. Making a classifier catch more cases (higher recall) usually means more false alarms (lower precision), and vice versa. This is the precision/recall trade-off.
The good news: you don't need to retrain the model to move along this trade-off. You just change one number — the decision threshold. This topic shows how.