| 18 | vector<float_type> predict_y; |
| 19 | |
| 20 | float |
| 21 | load_dataset_and_train(string train_filename, string test_filename, float_type C, float_type gamma, float_type nu) { |
| 22 | train_dataset.load_from_file(train_filename); |
| 23 | test_dataset.load_from_file(test_filename); |
| 24 | param.gamma = gamma; |
| 25 | param.C = C; |
| 26 | param.nu = nu; |
| 27 | param.kernel_type = SvmParam::RBF; |
| 28 | std::shared_ptr<SvmModel> model; |
| 29 | model.reset(new NuSVR()); |
| 30 | model->train(train_dataset, param); |
| 31 | std::shared_ptr<Metric> metric; |
| 32 | metric.reset(new MSE()); |
| 33 | predict_y = model->predict(test_dataset.instances(), 100); |
| 34 | return metric->score(predict_y, test_dataset.y()); |
| 35 | } |
| 36 | }; |
| 37 | |
| 38 | TEST_F(NuSVRTest, test_set) { |
nothing calls this directly
no test coverage detected