# Green Classify Tool – F Score

The F-Score provides a weighted average of Recall (R) and Precision (P) values. The F-Score tends to be the best measure of the overall accuracy of the application.

Properties:

- F=1 only if P=1 and R=1
- F=0 only if P=0 or R=0
- In general, min(P,R) ≤ F ≤ max(P,R)
- Harmonic mean: 1/F = 0.5 (1/P + 1/R)

Optimization Concerns:

- To avoid false positives absolutely, target P=1
- To avoid false negatives absolutely, target R=1

Otherwise:

- For well-balanced problems, overall accuracy is okay.
- For unbalanced problems where sparse classes matter, prefer the F-score.
- Use the F-score averaged over all classes.
- Set the Processing Threshold parameter to 0% to avoid a varying rate of non-classified views.