The grouping settings work in conjunction to control how predictor grouping is established. The fact that a predictor has more groups typically increases the performance, but the model may become less robust.

• Grouping Granularity: a value between 0 and 1 that determines the granularity of predictor groups; higher values result in more groups, lower values in less groups. This setting establishes the threshold for a statistical measure that indicates the distinctive behavior between predictors groups. If the measure is above, the groups indicate significant distinctive behavior, otherwise they will be collapsed. Default setting is 0.25.
• Grouping Minimum Cases: a value between 0 and 1 that determines the minimum percentage of cases per interval. Higher values result in decreasing the number of groups, which may be used to increase the robustness of the model. Lower values result in increasing the number of groups, which may be used to increase the performance of the model. Default setting is 0.05.