Github user selvinsource commented on the pull request:
https://github.com/apache/spark/pull/9397#issuecomment-153474883
Here the diff between the two files (BinaryClass vs Class):
http://www.mergely.com/w7ufbahQ/
Practically the difference between the Binary and the Class version is that
instead of building two fixed regression tables (YES/NO), I create a Category
Zero table (the one without the predictors) and as many regression tables as
the number of the categories (numClasses-1).
The code, in case of numClasses = 2, does exactly what it was doing before
in the BinaryClassificationPMMLModelExport class that I originally wrote.
My spark validator project confirms both Binary and Multiclass pmml export
works fine:
https://github.com/selvinsource/spark-pmml-exporter-validator/tree/logistic_regression_multi_class
See sections:
Logistic Regression (Binary Classification)
Logistic Regression (Multiclass Classification)
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