Binary Classification, Confusion Matrix, Precision, Recall, F Score.
to false positive than false negative we select this β = 0.5 F-Score = (1+0.5²) (Precision * Recall) / 0.5²(Precision + Recall) = 1.25(Precision * Recall) / 0.25(Precision + Recall) F2 Score— Here False negative is more important than Flase positive. F-Score = (1+β²) (Precision * Recall) /