Home > Testing and Tuning Models > Testing Classification Models > Classification Model Test V... > Tuning Classification Models > How to Tune Classification ... > ROC > ROC Tuning Steps
ROC tuning usually follows these steps:
In the Property Inspector for the build node, go to the Models tab. Select the model that you want to tune and click
Select Tune from the menu. The Tune Settings dialog opens in a new tab. In Tune Settings, go to the ROC tab.
Select a target value. In the case of ROC, there are only two values.
Select a custom operating point if you do no want to use the default point. See Select Custom Operating Point.
Select the kind of Performance Matrix to use. The default is Overall Accuracy; you can also choose Average Accuracy, Custom Accuracy, or Model Accuracy.
If you select Custom Accuracy, fill in the values for the performance matrix.
Click Tune, below the Performance Matrix. New Tune Settings are displayed in the same panel as the Performance Matrix.
Examine the Derived Cost Matrix. You can continue tuning by changing any selections that you made.
To cancel the tuning, click Reset. Tuning returns to Automatic.
When you done tuning, either click OK to accept the tuning or Cancel to cancel.
To see the impact of the tuning, re- the model node.