[SOLVED]The prediction score are different between the Rapidminer and Libsvm

What exactly do you mean by scoring? How did you evaluate it? If you have a RapidMiner process, please post it here.
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

Hi,

your processes look fine. Actually I don't know why exactly the confidences are different. Which version of libSVM are you using?
Did you use exactly the same training and test data with the same preprocessing for training and applying the SVM from the library?

Best, Marius

Hi,
Besides using libsvm module in Rapidminer, I used libsvm(version 3.12) as the comparison. Both experiments used the same training and test data set. The data pre-processing steps are also the same for both experiments.

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.

Marius, Thanks. I changed the option from "confidence to multiclass" to "confidence calculation".

And, just for the records, now the results are equal?

yes, the SVM score gotten from Rapidminer matches the LIBSVM command line very well. Thanks.