Home > Model Nodes > Association Node > Classification Node > Edit Classification Build Node > Classification Node Properties > Classification Node Test
The test section specifies the data used for test and which tests to perform.
For more information about testing classification nodes, see Testing Classification Models.
You can specify no test.
The default is to test all models built using the test data that is created by randomly splitting the build data into two subsets.
By default, the test node performs these tests:
Performance Metrics
Confusion Matrix
ROC Curve (Binary Class only)
Lift and Profit
Lift and profit for the top 5 target classes by frequency. Click Edit to change the selected values as described in Target Values Selection.
If you plan to tune the models, you must test the models in the build node, not in a Test node. You should also select Generate Selected Test Results for Tuning. See Tuning Classification Models for details.
Test Data is created is one of the following ways:
Use Split Build Data for Testing with the Split for Test 40%; the Split creates a Table that is Parallel. This is the default.
You can change the percent of the Split for Test, create a View, or deselect parallel.
Use all of the Mining Build Data for Testing
Use a Test Data Source for Testing
You can provide a separate test data source;. Select Use Test Data Source for Testing and connect the test data source to the build node after you connect the build data.
Another way to test a model is to use a Test Node.