LIBSVMLearner

LIBSVM v2.89 is an integrated software for support vector classification. For a more detailed description - especially of the parameters - see the webpage.

Options

Type of SVM
Set type of SVM (default is C-SVM) C-SVC, nu-SVC, one-class SVM, epsilon-SVR, nu-SVR.
Kernel
Set type of kernel function (default is polynomial).
  • linear: u'*v
  • polynomial: (gamma*u'*v + coef0)^degree
  • radial basis function: exp(-gamma*|u-v|^2)
  • sigmoid: tanh(gamma*u'*v + coef0)
Degree
Set degree in kernel function.
Gamma
Set gamma in kernel function (a good value is 1/nrAttributes).
Coef0
Set coef0 in kernel function.
Cost
Set the parameter C of C-SVC, epsilon-SVR, and nu-SVR.
Nu
Set the parameter nu of nu-SVC, one-class SVM, and nu-SVR.
Loss-Epsilon
Set the epsilon in loss function of epsilon-SVR.
Cachesize
Set cache memory size in MB.
Epsilon
Set tolerance of termination criterion.
Shrinking
Whether to use the shrinking heuristics.
Probability estimates
Whether to train a SVC or SVR model for probability estimates.
Target column
The target column, can be nominal for classification or numerical for regression.

Input Ports

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DataTable containing the training data. Keep in mind that the computational complexitiy is in O(n^2), therefore do not use more than 15.000 rows.

Output Ports

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The trained SVM model in LIBSVM format.

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