Binary Classification, Confusion Matrix, Precision, Recall, F Score.
(Precision + Recall) = 2 (Precision * Recall) / (Precision + Recall) F0.5 Score — Here False positive is more important than Flase negative. F-Score = (1+β²) (Precision * Recall) / β²(Precision + Recall) // Here you will try to decrease your β value. // This means you are providing more important