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Binning numeric predictors

Updated on March 11, 2021

Generate bins over which you want to distribute numeric predictors. Binning allows you to group cases into bins of equal volume or width.

The bins of equal width are simpler to manage and easy to understand. The bins of equal volume scale data well, handle skewness better, but are difficult to use with categorical data.
  1. In the Data analysis step, click a numeric predictor.
  2. In the predictor workspace, click the Binning tab.
  3. In the Minimum value field, enter the threshold value of the lowest value bin.
    Values lower than the minimum value belong to the lowest bin.
  4. In the Maximum value field, enter the threshold value of the highest value bin.
    Values higher than the maximum value belong to the highest bin.
  5. In the Number of intervals field, enter the number of intervals over which the values of predictors will be analyzed.
  6. In the Binning type list, select whether you want to create intervals with equal volume or width.
  7. Click Add special value to add a value that you want to exclude from the bins. Click Apply. Typically, special values represent error codes.
  8. Optional: To read the data in a graph or a table, click the Graphical view tab or the Tabular view tab.
  9. Confirm your updates by clicking Submit.

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