How to use

setKernel

method

in

org.dmg.pmml.support_vector_machine.SupportVectorMachineModel

@Override
public SupportVectorMachineModel encodeModel(Schema schema){
  int[] shape = getSupportVectorsShape();
  int numberOfVectors = shape[0];
  int numberOfFeatures = shape[1];
  List<Integer> support = getSupport();
  List<? extends Number> supportVectors = getSupportVectors();
  List<? extends Number> dualCoef = getDualCoef();
  List<? extends Number> intercept = getIntercept();
  SupportVectorMachineModel supportVectorMachineModel = LibSVMUtil.createRegression(new CMatrix<>(ValueUtil.asDoubles(supportVectors), numberOfVectors, numberOfFeatures), SupportVectorMachineUtil.formatIds(support), ValueUtil.asDouble(Iterables.getOnlyElement(intercept)), ValueUtil.asDoubles(dualCoef), schema)
    .setKernel(SupportVectorMachineUtil.createKernel(getKernel(), getDegree(), getGamma(), getCoef0()));
  return supportVectorMachineModel;
}

@Override
public SupportVectorMachineModel encodeModel(Schema schema){
  int[] shape = getSupportVectorsShape();
  int numberOfVectors = shape[0];
  int numberOfFeatures = shape[1];
  List<Integer> support = getSupport();
  List<? extends Number> supportVectors = getSupportVectors();
  List<Integer> supportSizes = getSupportSizes();
  List<? extends Number> dualCoef = getDualCoef();
  List<? extends Number> intercept = getIntercept();
  SupportVectorMachineModel supportVectorMachineModel = LibSVMUtil.createClassification(new CMatrix<>(ValueUtil.asDoubles(supportVectors), numberOfVectors, numberOfFeatures), supportSizes, SupportVectorMachineUtil.formatIds(support), ValueUtil.asDoubles(intercept), ValueUtil.asDoubles(dualCoef), schema)
    .setKernel(SupportVectorMachineUtil.createKernel(getKernel(), getDegree(), getGamma(), getCoef0()));
  List<SupportVectorMachine> supportVectorMachines = supportVectorMachineModel.getSupportVectorMachines();
  for(SupportVectorMachine supportVectorMachine : supportVectorMachines){
    String category = supportVectorMachine.getTargetCategory();
    // LibSVM: (decisionFunction > 0 ? first : second)
    // PMML: (decisionFunction < 0 ? first : second)
    supportVectorMachine.setTargetCategory(supportVectorMachine.getAlternateTargetCategory());
    supportVectorMachine.setAlternateTargetCategory(category);
  }
  return supportVectorMachineModel;
}

supportVectorMachineModel.setKernel(svmKernel.createKernel(degree.asScalar(), gamma.asScalar(), coef0.asScalar()));