Confusion Matrix, Accuracy, Recall, Precision.
Negatives (TN), False Positives (FP), and False Negatives (FN). 2. Interpretation of Confusion Metrics: To interpret confusion metrics effectively, we need to understand the metrics derived from the matrix: Accuracy: It measures the overall correctness of the model’s predictions. - Precision: It