What is the F1 score and how do I interpret it?

What is the F1 score and how do I interpret it?

The F1 score is a measure of a model's accuracy that considers both precision and recall. It's the harmonic mean of the two.

Why is the F1 score important in evaluating models?

The F1 score is crucial when you have imbalanced classes, as it provides a better measure of the model's performance than accuracy alone.

How do I calculate the F1 score?

You can calculate the F1 score using the formula: F1 = 2 * (precision * recall) / (precision + recall).

Can you give me an example of F1 score calculation?

Sure! If your model has a precision of 0.8 and a recall of 0.6, the F1 score would be 2 * (0.8 * 0.6) / (0.8 + 0.6) = 0.69.