I have been working in R the last few weeks and have been tinkering with forecasting/predicting values for the financial data.

Is there a good place to find out what the different variables represent? Such as m in caret package, size. C, degree, sigma, and scale.

For example I am trying to use the Support Vector Machines models in caret but they require some input parameters for the different types.

`Support Vector Machines type, package, variables svmLinear, kernlab, C svmRadial, kernlab, C, sigma svmRadialCost, kernlab, C svmPoly, kernlab, degree, scale, C `

I found the above in documentation regarding the SVM Models in the caret package. However, no explanation on what the variables mean….

Would there be a good place to figure out what these variables mean? Or are they already meant to be known by even novices? If so where can I find out about them?

I think it would be best if I knew what these were instead of just changing them randomly.

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#### Best Answer

The parameters you're describing are standard kernel parameters in SVM classification. I almost always forget what they mean too, but have found the LibSVM website to be a solid reference for this. From the site, linear is the cost parameter, which is appears in every kernel, and

$$text{Linear: } u'*v$$ $$text{Polynomial: } (gamma*u'*v + coef_{0})^{degree}$$ $$text{RBF: } exp^{(-gamma*|u-v|^{2})}$$ $$text{Sigmoid: } tanh(gamma*u'*v + coef_{0})$$

Does that help?

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