Help with SVM algorithm (under optimization loop)

Dear Knimers,

I need help with my workflow on an SVM optimization loop. I applied the RBF kernel, and added two parameters, using a series of different ranges of values (from very tiny to widely broad spectra): a) sigma; and b) Overlapping penalty.

This is what my workflow looks like:

These are my data:

Help with PpredictionsClassifcations.xlsx

And this is the Confusion Matrix I always get, no matter what parameters I choose (in the Start node):

Can someone help me to find out what am I doing wrong? The predictions I get are almost always the same, and almost all are grouped under just one class…

Thanks for any help.

B.R.,

Rogério.