SVM's classificationMethod is always "OneAgainstOne" about jpmml-converter HOT 3 CLOSED

@rymmonlu What exactly is the problem? Is the generated PMML document making incorrect predictions?

What difference does it make how a Python data structure is translated to a PMML data structure, for as long as the translation preserves the properties of the original prediction algorithm?

from jpmml-converter.

I've now run my SVC integration tests with decision_function_shape="ovr" and decision_function_shape="ovo", and verified that the current JPMML-Converter/JPMML-SkLearn/SkLearn2PMML software stack is generating PMML documents that make correct predictions when evaluated with the JPMML-Evaluator library.

The JPMML family of libraries chooses to use ONE_AGAINST_ONE encoding scheme for LibSVM-based SVM models, because it leads to the most compact/readable PMML representation.

from jpmml-converter.

Thanks for your confirm about the "ONE_AGAINST_ONE".
BTW, my prediction result looks ok just as you tried.

from jpmml-converter.