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.

1. 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.
2. In the Show parameter list, select the model output that is used to plot data.
3. 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.
4. In the Reclassified score distribution chart, check the aggregated results.
5. 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.
6. Click Save.