ROC Curve tools¶
The ROC Curve tab provides tools for exploring classification, performance, and statistics related to a selected model at any point on the probability scale. The following topics show how to use these tools:
| Topic | Description |
|---|---|
| Use the ROC Curve tools | Accessing the ROC Curve tab and understanding its components. |
| Select data and display threshold | Setting the data source and display threshold used for ROC Curve visualizations. |
| Confusion matrix | Using a confusion matrix to evaluate model accuracy by comparing actual versus predicted values. |
| Prediction Distribution graph | Viewing the distribution of actual values in relation to the display threshold. |
| ROC curve | Using a ROC curve to view a plot of the true positive rate against the false positive rate for given data source. |
| Profit curve | Generating a profit curve to estimate the business impact of a selected model. |
| Cumulative charts | Generating charts to help assess a model's cumulative characteristics. |
| Custom charts | Generating your own charts to explore classification, performance, and statistics for a model. |
| Metrics | Viewing statistics that describe model performance at the selected display threshold. |
Updated January 3, 2025
Was this page helpful?
Great! Let us know what you found helpful.
What can we do to improve the content?
Thanks for your feedback!