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Decision function computed doesn't match with sklearn.svm.SVC
Hi,
I train my SVC in Python and port it to C++ as follows:
with open(fname, "w") as f: f.write(port(clf))
However, the decision function computed by clf.decision_function(X)
(in Python) and the one computed inside Eloquent::ML::Port::SVM::predict
(in the generated header file) do not match. The predictions do not match.
Is there something I'm missing?
hi, i am also using micromlgen to convert my RF regression into C++ code. but the generated code gives different and wrong results as compared to the python code i had written. it is giving a single output for every input given to it which in fact is wrong.
Can someone tell me what went wrong?