Last updated: Oct 09, 2024
- Add a Data Asset node that points to property_values_train.csv.
- Add a Type node, and select
taxable_valueas the target field (Role = Target). Other fields will be used as predictors.Figure 1. Setting the measurement level and role 
- Attach an Auto Numeric node, and select Correlation as the metric used to rank models (under BASICS in the node properties).
- Set the Number of models to use to 3. This means
that the three best models will be built when you run the node.
Figure 2. Auto Numeric node BASICS 
- Under EXPERT, leave the default settings in place. The node will estimate
a single model for each algorithm, for a total of six 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 under BASICS, the node will calculate the accuracy of the six algorithms and build a single model nugget containing the three most accurate.
Figure 3. Auto Numeric node EXPERT options 
- Under ENSEMBLE, 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.
