The Score distribution chart on the Predictive model tab displays a nonaggregated
classification of a predictive model's results. The chart is available for predictive models
that you build in Pega Platform.
You can use the chart to reclassify the score distribution to
business-defined classes according to your needs. For example, the score distribution can be
mapped from 10 deciles to three classes of distinct predicted behavior, such as high, medium,
or low risk of churn. Remapping the classification that is defined in the predictive model to
the smaller number of business strategies allows you to assign actions to each of these
classes.
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Open a Predictive Model rule instance that you want to edit.
Note: The rule instance must contain a predictive model that was built in Pega Platform.
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In the Show parameter list, select the model output that is used
to plot data.
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In the Score distribution chart, click between the bars that
represent classes to aggregate them. A red bar indicates class aggregation.
Note: When you aggregate classes, you also aggregate their range result into one.
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In the Reclassified score distribution chart, check the
aggregated results.
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In the Classification groups section, change the values in the
Result column to map the classes output to decision
results.
For example, if you use a predictive model in a strategy to predict customer churn,
you need to aggregate the classes into three groups and label their results as high,
medium, and low, depending on the churn risk that they identify.
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Click Save.