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Thanks Sebastian,
I think that I am gaining a better understanding of how SVM may be used for regression. In RapidMiner, I am using the standard SVM operator. I have noticed for the different kernels that there are a variety of parameters. However, it does not seem as though there is much explanation of the significance of each parameter in the RapidMiner Wiki. If possible, could you please point me to any resource that would explain more about these parameters? Alternatively, can you offer a summary of the different parameters?
Thanks very much,
Phil
I think that I am gaining a better understanding of how SVM may be used for regression. In RapidMiner, I am using the standard SVM operator. I have noticed for the different kernels that there are a variety of parameters. However, it does not seem as though there is much explanation of the significance of each parameter in the RapidMiner Wiki. If possible, could you please point me to any resource that would explain more about these parameters? Alternatively, can you offer a summary of the different parameters?
Thanks very much,
Phil
this depends on the SVM implementation you use. The LibSVM needs to be switched to one of the SVR Modes (first parameter). The standard SVM does this automatically.
Greetings,
Sebastian