How can I use SMO classifier for three class classification? What parameters should I set?

[Pragya Sharma]

I came up with this issue because the weka.gui.GenericObjectEditor for SMO is a bit different from the video lecture(support vector machines 4.5). For example, there is no option of bulidLogisticModels and there are extra options for calibration, which contains the same classifier list as the classifiers.

I'm working on classification of EEG signals for three classes, N, SF, and S which stand for Normal, SeizureFree and Seizure, respectively. I converted the classified data and it classified well with default settings. But I intend to use SMO and not sure what to set with the parameters. Here is the list that appeared in my case:

If there's any further information required please let me know.