The IDLmlSVMPolynomialKernel class encapsulates SVM (Support Vector Machine) parameters that help define a polynomial kernel with the following formula:


Kernel = IDLmlSVMPolynomialKernel()
Model = IDLmlSupportVectorMachineClassification(2, 4, KERNEL=Kernel)


Kernel = IDLmlSVMPolynomialKernel([, Keywords=value])




BIAS (optional)

Set this keyword to a bias term in the kernel. The default value is 1.0.

GAMMA (optional)

Set this keyword to a gamma term in the kernel. The default value is 1 / NATTRIBUTES, but the optimal value for any particular model is highly variable and will likely need to be adjusted. You should perform a grid search for parameter selection as described in Hsu, Chang, and Lin (2010).


Chih-Chung Chang and Chih-Jen Lin, LIBSVM: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2:27:1--27:27, 2011. Software available at

Hsu, C.-W., C.-C. Chang, and C.-J. Lin. (2010). A practical guide to support vector classification. National Taiwan University.

Wu, T.-F., C.-J. Lin, and R. C. Weng. (2004). Probability estimates for multi-class classification by pairwise coupling. Journal of Machine Learning Research, 5:975-1005,

DEGREE (optional)

Set this keyword to a value greater than or equal to 1, indicating the degree of the polynomial kernel. The default value is 2.

Version History



See Also

IDLmlSVMLinearKernel, IDLmlSVMRadialKernel, IDLmlSVMSigmoidKernel