Predictive Model rule form
Completing the Results tab

The segmentation provided by the predictive model needs to be assigned to actions applying to a given class or class range. Defining predictive models depends on the type of model:

• PAD model
• PMML model

PAD Model

PAD models are constructed to generate the largest possible number of classes (segments) that exhibit predicted behavior, steadily increasing as the class number increases. However, business strategies translate to the two or three alternatives typically associated with the probability of predicted behavior (high, medium and low). Remapping the classification defined in the predictive model to the smaller number of business strategies allows you to increase the quality of business. For example, if a lower propensity class is reassigned to the medium propensity class where fewer customers are presented with a product offer but a greater proportion responds, although the volume of business decreases, the quality increases.

• Graphical representation
• Mapping segments

Graphical Representation

Graphical representation is provided for predictive model results. Two graphs side by side shows the score distribution.

• View Parameter: drop-down that allows you to selected the model output used to plot data. Use the data points to inspect the values.
• X-axis: visually represents the Classification. If you combine classes, they are also aggregated in the chart.
• Y-axis: visually represents the Percentage.

The graph on the left allows is based on the non-aggregated classification; this is also the graph displayed in the Statistics tab. As you aggregate classes, the graph on the right displays aggregated statistics according to the number of results.

Map Segments

Map the classes output by the model to decision results. To understand the effect of combining the different classes to create predictive based segmentation, examine the grouped statistics in the graph displayed on the right.

Note: If the original PAD model does not contain aggregation or grouping statistics information, N/A is displayed.

• By default, the Results tab displays the total number of classes corresponding to the segmentation created by the predictive model.
• You aggregate classes by clicking by placing your cursor between the bars corresponding to the class, and clicking so that classes up to that one can be binned under the same result. A red bar signals the class aggregation. Click Apply to reflect the changes, and the segments in the Result column. The graph on the right reflects the recalculated class distribution. Use Reset to set the class aggregation back to default so that you can restart the process of aggregating classes.

PMML Model

The results of a PMML model consist of model output fields. In this tab, you select the output field that provides the classification result. Typically, this is the model's default outcome field.

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