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Use this tab to configure how the Adaptive Decision Manager (ADM) operates by controlling the runtime throughput and the creation and update of the individual scoring models. The settings should be configured to appropriate values to prevent high loads on the database.

The settings are grouped by category — Responsiveness, Data Analysis and Advanced.

Field

Description
Responsiveness

Use this section to configure the memory setting.
Memory

This setting corresponds to the value that specifies the amount of interaction results history, which are translated in number of cases, the scoring models maintain during predictions. By default, it is set to 0.

The memory configuration allows you to discard the oldest cases, and it allows you to implement trend detection by creating multiple adaptive models, all triggered by the same proposition. This setting influences the binning of predictors as behavior changes with new cases being recorded.

  • Low memory values allow the identification of new trends.
  • High memory values provide robust and long-term predictive power.
  • Set the memory to 0 to never discard information.
Data Analysis

Use this section to configure the settings that influence data analysis
Run Data Analysis After

The value that determines the number of interaction results that trigger running data analysis for a model. Data analysis is triggered after the number of interaction results configured in this setting is reached. Default setting is 500.
Grouping Granularity

A value between 0 and 1 that determines the granularity of predictor groups. Default setting is 0.25.
Grouping Minimum Cases

A value between 0 and1 that determines the minimum percentage of cases per interval. Default setting is 0.05.
Performance Threshold

A value between 0 and1 that determines the threshold for excluding poorly performing predictors. Default setting is 0.52.
Correlation Threshold

A value between 0 and 1 that determines the threshold for excluding correlated predictors. Default setting is 0.8.
Advanced Configuration

Use this section to configure the settings that control other operations performed in the ADM database.
Performance Memory

A value that determines the number of cases of moving window size per proposition. The number of cases of moving window size per proposition influences the calculation of the CoC, and it is implemented so that equal comparison between models can be performed. Default setting is 0. Select an existing property to map to the field or click Edit itemto create a new property and map it.
Refresh After

A value that determines the number of interaction results that trigger refreshing the scoring models in the ADM database. Model refresh is performed when the number of interaction results in this settings is reached. You should set this value to a value lower than the value for running data analysis. Default setting is 500.
Enable Local Updates

Check to enable or disable updating the model's local profile after every response. This setting allows you to enable local (PRPC) learning for the adaptive models configured by the adaptive model rule. The default setting is enabled.
Audit Notes

Check if you want adaptive model details captured in the work object's history. Default setting is disabled.

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