Interpreting a confusion matrix involves understanding various performance metrics that can be derived from it. These metrics include: - Accuracy: The proportion of true results (both true positives and true negatives) among the total number of cases examined. - Sensitivity (Recall or True Positive Rate): The proportion of actual positives correctly identified. - Specificity (True Negative Rate): The proportion of actual negatives correctly identified. - Precision (Positive Predictive Value): The proportion of positive results that are true positives.
