| 237 | } |
| 238 | |
| 239 | int dense_predict(int row_size, int features, float* data, SvmModel *model, float* predict_label, int verbose){ |
| 240 | if(verbose) |
| 241 | el::Loggers::reconfigureAllLoggers(el::ConfigurationType::Enabled, "true"); |
| 242 | else |
| 243 | el::Loggers::reconfigureAllLoggers(el::ConfigurationType::Enabled, "false"); |
| 244 | DataSet predict_dataset; |
| 245 | predict_dataset.load_from_dense(row_size, features, data, (float*) NULL); |
| 246 | vector<float_type> predict_y; |
| 247 | predict_y = model->predict(predict_dataset.instances(), -1); |
| 248 | for (int i = 0; i < predict_y.size(); ++i) { |
| 249 | predict_label[i] = predict_y[i]; |
| 250 | } |
| 251 | return 0; |
| 252 | } |
| 253 | |
| 254 | int n_sv(SvmModel* model){ |
| 255 | return model->total_sv(); |
nothing calls this directly
no test coverage detected