SVM learner parameter


I am trying to optimize the performance of the SVM learner using a polynomial kernel

  • Polynomial (has three parameters)
    • Power
    • Bias
    • Gama

could someone kindly explain to me, the concept of these three terms?

Hello @degapifa

Welcome to the KNIME forum.

This previous post by @ScottF may help to answer your question:

Hope this is of help :slight_smile:

Best regards,



thanks for the answer, I can’t understand the parameter: power corresponds to p in the frist formula?

p is the power, yes. You can read more about the effects of gamma on various kernels (including polynomial) in this recent paper:


thanks for the answer. It is a really good job to increase understanding. One last thing that i have noticed: i should optimize the cost C. In the SVM node in knime would it be equivalent to overlapping penalty?

I believe so, yes (although I should verify that internally).

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