Building the Stream
- Add a Statistics File
source node pointing to property_values_train.sav, located in the Demos folder of your
IBM® SPSS® Modeler installation. (You can specify
$CLEO_DEMOS/in the file path as a shortcut to reference this folder. Note that a forward slash—rather than a backslash—must be used in the path, as shown. )Figure 1. Reading in the data 
- Add a Type node, and select taxable_value as the target field (Role =
Target). Role should be set to Input for all other
fields, indicating that they will be used as predictors.
Figure 2. Setting the target field 
- Attach an Auto Numeric node, and select Correlation as the metric used to rank models.
- Set the Number of models to use to 3. This means that
the three best models will be built when you execute the node.
Figure 3. Auto Numeric node Model tab 
- On the Expert tab, leave the default settings in place; the node will
estimate a single model for each algorithm, for a total of seven models. (Alternatively, you can
modify these settings to compare multiple variants for each model type.)
Because you set Number of models to use to 3 on the Model tab, the node will calculate the accuracy of the seven algorithms and build a single model nugget containing the three most accurate.
Figure 4. Auto Numeric node Expert tab 
- On the Settings tab, leave the default settings in place. Since this is a continuous target, the ensemble score is generated by averaging the scores for the individual models.
