01 · Understand the idea
In simple words
Think about a lost-item search. Precision asks how many items you brought back were the right kind. Recall asks how many of all the right items you managed to find. A system can be cautious and precise while missing many valid items. Which error matters more depends on the task.
Two useful terms
False positive: an incorrect positive prediction. False negative: a positive case the system missed.
Build your understanding
Precision asks how many positive predictions were correct. Recall asks how many actual positives were found. They answer different questions, so neither should be interpreted alone. The right trade-off depends on the cost of false alarms and missed cases.
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