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Checking score distribution

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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.

  1. In the Score distribution step, select a model for analysis.

  2. Optional:

    To analyze distribution of a field across the scoreband, click Select cross tab field, select a field, and click Submit.

  3. Modify the division of scores by expanding the Score distribution settings section and selecting a segmentation method:

    If Then
    If you want to create the specified number of score bands or bands with the specified percentage of cases in each band, perform the following actions:
    1. From the Segmentation method drop-down list, select Create bands with equal number of cases.
    2. In the Max. # of bands field, enter the number of bands.
    3. In the Number field, enter the number of cases per band.
    4. In the Percentage field, enter the percentage of cases per band.
    The cases can be restricted to those with a specified outcome.
    If you want 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, perform the following actions:
    1. From the Segmentation method drop-down list, select Create statistically significant bands.
    2. From the Function column drop-down list, select a method for creating bands.
    3. In the Max. probability of a spurious difference field, enter the maximum difference between bands, expressed in likelihood.

      The value must be between 0 and 1.

    4. In the Minimum size field, enter the minimum size of each band.

      The number is a percentage of the sample.

    If you want to create score bands with a minimum number of records and monotonically increasing values in terms of the specified field, perform the following actions:
    1. From the Segmentation method drop-down list, select Create monotonically increasing bands.
    2. From the Function column drop-down list, select a method for creating bands.
    3. In the Minimum size field, enter the minimum size of each band.

      The number is a percentage of the sample.

    If you want to define your own score bands, perform the following actions:
    1. From the Segmentation method drop-down list, select Create user defined bands and click Apply.
    2. On the Graphical view tab mark your segments on the graph by clicking on the curve.

      Base your segments on the Score band cutoff score in the Tabular view.

  4. Optional:

    On the Graphical view tab or Tabular view tab, check the score distribution analysis of the selected models.

  5. Optional:

    Analyze additional fields across the scorebands to make secondary predictions:

    1. Click the Tabular view tab.

    2. Click Select cross tab field.

    3. In the Select additional fields dialog box, select the fields that you want to analyze and click Submit.

    Secondary predictions can provide a valuable insight into customer activity and business economics.
    You can calculate average sales value, cost, and contribution.
  6. Move to the next step by clicking Next.

  • Analyzing models

    In the Model analysis step you can compare and view scores of one or more predictive models in a graphical representation, analyze predictive models' score distribution, and compare the classification of scores of one or more predictive models.

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