[SOLVED]The prediction score are different between the Rapidminer and Libsvm
I ran the SVM classification using both Rapidminer and Libsvm against the same data set. In the rapidminer, I also used the libsvm implementation. The document processing scheme and svm parameter setting are exactly the same for both experiment. However, the generated score are different. Are there any possible reasons to cause this kind of different?
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Then you are using a different major version of libSVM than is integrated into RapidMiner. That could play a role in the different values. Furthermore, I saw that there are different methods for getting predictions, like predict_values, predict_sigmoid_values etc. Maybe you (or the tool you are using) use different methods than RapidMiner does. I am not an expert for the details of the libSVM though, but you can have a look at the implementation in the class LibSVMModel in the RapidMiner source code.
Maybe it's also a version issue: I am not absolutely sure, but by a first quick glance it seems that the version of libSVM integrated into RapidMiner is based on v2.84.
Finally, what are the actual scores that you retrieved?
Best,
Marius