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Beschreibung
By default, if you train a PySparkML model with a dataframe that has uppercase column names, and then try to run an inference with the same column names but in lowercase, the prediction will fail. Is there a parameter or way to set case insensitivity on inference?
I see this checking for a strict vs relaxed select of the leapframe which I assume is what I'm looking for. How can I set that when serializing a PySpark Model to an MLeap Bundle?
Thanks!
Edit: I see that my second question was wrong - It comes from the transform function, not embedded into the Bundle itself. So when I call model.transform(frame) is there documentation on how to pass in the relaxedSelect option?
Edit: It seems like I'm incorrect on what relaxedSelect does. It seems to just "not throw an error on columns that don't exist" instead of being case insensitive. Is there a case insensitivity option?