- Precision : This tells when you predict something positive, how many times they were actually positive. whereas,
- Recall : This tells out of actual positive data, how many times you predicted correctly.
Having said above, in case of spam email detection, One should be okay if a spam email (positive case) left undetected and doesn’t go to spam folder but , if an email is good (negative), then it must not go to spam folder. i.e. Precison is more important. (If model predicts something positive (i.e. spam), it better be spam. else, you may miss important emails).
- For rare cancer data modeling, anything that doesn’t account for false-negatives is a crime. Recall is a better measure than precision.