Score distribution allows you to analyze how a predictive model segments the cases in the population. Typically, the range of scores is broken intro intervals with increasing likelihood of positive type of behavior. The behavior is based on the behavior of the cases in the development sample that fall into each interval.
With model analysis based on score distribution, you can compare predictive models based on consistent terms, for example, how they distribute cases over 10 equal scorebands. The more predictive power of the model, the more distinct the bands are in terms of their performance. You can also generate model reports and analyze score distribution.
In the Score distribution step, select a model for analysis.
Unfold the Score distribution settings section and select a segmentation method. This method controls the division of scores.
Create bands with equal numbers of cases - Select to create the specified number of score bands or bands with the specified percentage of cases in each band. The cases can be restricted to those with a specified outcome.
Create statistically significant bands - Select to create different score bands in terms of their specified behavior and statistical criteria in terms of the maximum probability that the difference between two bands is spurious, and that there is a minimum number of records in each band.
Create monotonically increasing bands - Select to create score bands with a minimum number of records and monotonically increasing values in terms of the specified field.
Create user defined bands - Select to define your own score bands. Based on the cut-off score in the table view, plot your own desired amount of segments. Bring the cursor on the plotted-graph and click the mouse button. To delete segments, use the button in the Graphical view tab or Table view tab.
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