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# Metrics¶

The Metrics pane, on the bottom right of the ROC Curve tab, contains a number of standard statistics that DataRobot provides to help describe model performance at the selected display threshold: The Metrics pane displays three metrics at a time, initially F1 Score, True Positive Rate (Sensitivity), and Positive Prediction Value (Precision). You can view different metrics by clicking Select metrics. If you select a metric from the list, it becomes one of the three displayed metrics. Note that you can only select three metrics to display, so if three are already selected, uncheck one to select a new metric. The new metrics display the next time you access the ROC Curve tab for any model until you change them.

The following table provides a brief description of each statistic, using Classification use case 1 to illustrate.

Statistic Description Sample (from use cases) Calculation
F1 Score A measure of the model's accuracy, computed based on precision and recall. N/A True Positive Rate (TPR) Sensitivity or recall. The ratio of true positives (correctly predicted as positive) to all actual positives. What percentage of diabetics did the model correctly identify as diabetics? False Positive Rate (FPR) Fallout. The ratio of false positives to all actual negatives. What percentage of healthy patients did the model incorrectly identify as diabetics? True Negative Rate (TNR) Specificity. The ratio of true negatives (correctly predicted as negative) to all actual negatives. What percentage of healthy patients did the model correctly predict as healthy? Positive Predictive Value (PPV) Precision. For all the positive predictions, the percentage of cases in which the model was correct. What percentage of the model’s predicted diabetics are actually diabetic? Negative Predictive Value (NPV) For all the negative predictions, the percentage of cases in which the model was correct. What percentage of the model’s predicted healthy patients are actually healthy? Accuracy The percentage of correctly classified instances. What is the overall percentage of the time that the model makes a correct prediction? Matthews Correlation Coefficient Measure of model quality when the classes are of very different sizes (unbalanced). N/A formula
Average Profit Estimates the business impact of a model. Displays the average profit based on the payoff matrix at the current display threshold. If a payoff matrix is not selected, displays N/A. What is the business impact of readmitting a patient? formula
Total Profit Estimates the business impact of a model. Displays the total profit based on the payoff matrix at the current display threshold. If a payoff matrix is not selected, displays N/A. What is the business impact of readmitting a patient? formula

Updated October 11, 2021