Predictive accuracy is often quantified using various statistical measures. Some of the most common metrics include:
Sensitivity (True Positive Rate): The proportion of actual positives correctly identified. Specificity (True Negative Rate): The proportion of actual negatives correctly identified. Positive Predictive Value (PPV): The proportion of positive results that are true positives. Negative Predictive Value (NPV): The proportion of negative results that are true negatives. Area Under the Curve (AUC): A measure of the model’s ability to distinguish between classes.
