public static void testSVMWrapperPackage() //rafal parsal
{
libSVM_Problem Problem = libSVM_Problem.Load("../../../LibSVMFull/testSvmWrapper/data/train.dat");
GuiPreferences.Instance.setLog("trainnig data loaded");
//GuiPreferences.Instance.setLog("trainnig data loaded";
Problem.Save("../../../LibSVMFull/testSvmWrapper/data/train_saved");
GuiPreferences.Instance.setLog("training data saved");
libSVM_Parameter Parameter = new libSVM_Parameter();
libSVM_Extension svm = new libSVM_Extension();
Parameter.svm_type = SVM_TYPE.C_SVC;
Parameter.kernel_type = KERNEL_TYPE.LINEAR;
svm = new libSVM_Extension();
svm.Train(Problem, Parameter);
libSVM_Problem Test = libSVM_Problem.Load("../../../LibSVMFull/testSvmWrapper/data/test.dat");
svm.GetAccuracyFromTest(Test);
double accuracy = svm.output.accuracy;
GuiPreferences.Instance.setLog("Predicted accuracy from testing set: " + accuracy.ToString());
svm.Dispose();
svm = new libSVM_Extension();
//svm.TrainAuto(10, Problem, Parameter, libSVM_Grid.C(), libSVM_Grid.gamma(), libSVM_Grid.p(), libSVM_Grid.nu(), libSVM_Grid.coef0(), libSVM_Grid.degree());
libSVM_Grid grid = new libSVM_Grid();
accuracy = svm.TrainAuto(10, Problem, Parameter, grid, null, null, null, null, null);
GuiPreferences.Instance.setLog("Predicted accuracy from 10 cross fold validation: " + accuracy.ToString());
svm.Save("../../../LibSVMFull/testSvmWrapper/data/model_file");
GuiPreferences.Instance.setLog("10 cfv best model saved");
svm.Dispose();
}
public void setDegreeGridSearchLong()
{
grid = libSVM_Grid.degree();
}
public void setCoef0GridSearchLong()
{
grid = libSVM_Grid.coef0();
}
public void setNuGridSearchLong()
{
grid = libSVM_Grid.nu();
}
public void setPGridSearchLong()
{
grid = libSVM_Grid.p();
}
public void setGammaGridSearchLong()
{
grid = libSVM_Grid.gamma();
}
public void setCGridSearchLong()
{
grid = libSVM_Grid.C();
}
