CSVFile f_feats_train("@SHOGUN_DATA@/classifier_4class_2d_linear_features_train.dat")
CSVFile f_feats_test("@SHOGUN_DATA@/classifier_4class_2d_linear_features_test.dat")
CSVFile f_labels_train("@SHOGUN_DATA@/classifier_4class_2d_linear_labels_train.dat")
CSVFile f_labels_test("@SHOGUN_DATA@/classifier_4class_2d_linear_labels_test.dat")

#![create_features]
Features features_train = features(f_feats_train)
Features features_test = features(f_feats_test)
Labels labels_train = labels(f_labels_train)
Labels labels_test = labels(f_labels_test)
#![create_features]

#![create_kernel]
Kernel kernel_gaussian = kernel("GaussianKernel")
kernel_gaussian.put("log_width", 2.1)
#![create_kernel]

#![choose_strategy]
MulticlassStrategy one_vs_rest=multiclass_strategy("MulticlassOneVsRestStrategy")
#![choose_strategy]

#![create_classifier]
Machine classifier = machine("LibSVM")
classifier.put("epsilon",1e-5)
#![create_classifier]

#![create_machine]
Machine mc_class =  machine("KernelMulticlassMachine",one_vs_rest,kernel_gaussian,classifier,labels_train)
#![create_machine]

#![train_and_apply]
mc_class.train(features_train)
Labels labels_predict = mc_class.apply_multiclass(features_test)
#![train_and_apply]

# integration testing variables
RealVector output = labels_predict.get_labels()