F1 Score
In plain terms
The harmonic mean of precision and recall.
Going deeper
The F1 score combines precision and recall into one number, useful when you need a balance and classes are imbalanced. It rewards models good at both.
Under the hood
Harmonic mean punishes imbalance between the two; preferred over accuracy on skewed data.
Examples
Imbalanced classification, model comparison, evaluation, NLP tasks.
Think of it like...
Like a combined grade that only stays high if you do well on both halves of the test.