Fmeas
F-measure, commonly referred to as the F1 score in its standard form, is a performance metric used to evaluate binary (and multi-class) classification tasks. It combines precision and recall into a single value, the harmonic mean of the two, which helps to balance the trade-off between correctly identifying positives and avoiding false positives.
Precision measures the proportion of predicted positives that are true positives, while recall measures the proportion
The general F-measure with a beta parameter is defined as F_beta = (1 + beta^2) * precision * recall / (beta^2
F-measure ranges from 0 to 1, with 1 indicating perfect precision and recall. It is widely used