private static SupportVectorRegressionSolution SvmGridSearch(IRegressionProblemData problemData, out svm_parameter bestParameters, out int nSv, out double cvMse)
{
bestParameters = SupportVectorMachineUtil.GridSearch(out cvMse, problemData, svmParameterRanges, numberOfFolds, shuffleFolds, maximumDegreeOfParallelism);
double trainingError, testError;
string svmType = svmTypes[bestParameters.svm_type];
string kernelType = kernelTypes[bestParameters.kernel_type];
var svm_solution = SupportVectorRegression.CreateSupportVectorRegressionSolution(problemData, problemData.AllowedInputVariables, svmType, kernelType,
bestParameters.C, bestParameters.nu, bestParameters.gamma, bestParameters.eps, bestParameters.degree, out trainingError, out testError, out nSv);
return(svm_solution);
}
/***************************************************/
public static PyObject ToPython(this SupportVectorRegression regressor)
{
return(regressor.SkLearnModel);
}
/*************************************/
public static Tensor Infer(SupportVectorRegression model, Tensor x)
{
return(new Tensor(BH.Engine.MachineLearning.Base.Compute.Invoke(System.Reflection.MethodBase.GetCurrentMethod().DeclaringType.Namespace, "SupportVectorRegression.infer", model, x)));
}
