Prediction accuracy can be evaluated using various metrics, such as:
1. Accuracy: The proportion of true results (both true positives and true negatives) among the total number of cases examined. 2. Sensitivity (Recall): The ability of the model to correctly identify patients with cancer. 3. Specificity: The ability of the model to correctly identify patients without cancer. 4. Precision: The proportion of true positive results among all positive results. 5. Area Under the Receiver Operating Characteristic Curve (AUC-ROC): A performance measurement for classification problems at various threshold settings.
