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Decision analytics and business rules

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Components in the business rules and decision analytics categories typically use customer data to segment cases based on characteristics and predicted behavior and place each case in a segment or score. Some common configuration applies to these components.

  • Select if the component should be defined on the Applies To class or the Strategy Result class for predictive model, scorecard, decision tree, decision table and matrix components.
    • Applies To: the component is evaluated one time on the primary page of the current strategy.
    • Strategy Results: the component is evaluated on every incoming step page.
  • Predictive model and adaptive model components map the output of the corresponding decision rule to strategy properties through the Output Mapping tab. In the case of scorecard components, this is done through the Score Mapping tab.
  • Select the rule in the rule name field, or click the button to create a new rule of the applicable rule type. Depending on the type of component, the rule field name allows you to select a predictive model, scorecard, adaptive model, decision table, decision tree or map value.
    • Adaptive models, decision tables, decision trees and map values allow for defining parameters. When these rules are on the Applies To class, the parameter values can be set in the Define Parameters section that is displayed in the component's Properties dialog.
    • Through segment filtering connections, you can create segmentation trees. For example, you start by defining a strategy path for cases falling in the Accept segment and another one for cases falling in the Reject segment.

Business Rules

  • Decision Table components reference decision table rules that can be used to implement characteristic based segmentation by referencing a decision table using customer data to segment on a given trait (for example, salary, age and mortgage)
  • Decision Tree components reference decision tree decision rules. Decision tree rules can often be used for the same purpose as decision tables.
  • Map Value components reference map value rules that use a multidimensional table to derive a result (for example, a matrix rule that allocates customers to a segment based on credit amount and credit history).
  • Split components branch the decision results according to the percentage of cases the result should cover. These components are typically used to build traditional segmentation trees in strategies, allowing you to derive segments based on the standard segments defined by the results of other components in the business rules and decision analytics category. You define the result ( pxSegment ) and the percentage of cases to assign to that result.

Decision analytics

  • Adaptive model components in strategies provide segmentation based on adaptive models in ADM. These components reference instances of the Adaptive Model rule and provide additional.
    • In the Adaptive model tab, select the Adaptive Model rule instance and unfold the Model context section to view model identifiers of this rule instance.
      • If the Adaptive Model component is attached to any source components, the values for model identifiers can be set only through the source components.
      • If there is no source component attached to the Adaptive Model component, you need to set values for model identifiers. The fields should be set according to what the binary model that is created in ADM is going to model.
  • Predictive model components reference predictive model rules.
  • Scorecard model components reference scorecard rules.
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