libsvm differences in accuracy between cmd line, weka and matlab

Question

I'm doing some preliminary testing with 2 classes of vectors, trying to separate them with libsvm. I get a 78.2% correct ID rate in Matlab and at the cmd line (using libsvm), but in Weka I get around 95%.

No cross-validation was done in Weka; just trained model and then read in test dataset and classified it.

Can anyone offer an explanation? Thanks in advance.

Answer 1

If you didn't provide a separate Test Data , the validation Folds should be set, 10 or desired value. however, be sure that the same SVMType and kerneltype are being used in both program. by default Weka uses C-SVC with radial basis function.