(self, X)
| 359 | return self.predict_label |
| 360 | |
| 361 | def decision_function(self, X): |
| 362 | X = self._validate_for_predict(X) |
| 363 | n_binary_model = (c_int * 1)() |
| 364 | thundersvm.get_n_binary_models(c_void_p(self.model), n_binary_model) |
| 365 | self.n_binary_model = n_binary_model[0] |
| 366 | if not (self._impl in ['c_svc', 'nu_svc', 'one_class']): |
| 367 | print("Not support decision_function!") |
| 368 | return |
| 369 | if self._sparse: |
| 370 | dec_func = self._sparse_decision_function(X) |
| 371 | else: |
| 372 | dec_func = self._dense_decision_function(X) |
| 373 | return dec_func |
| 374 | |
| 375 | def _dense_decision_function(self, X): |
| 376 | X = check_array(X, dtype=np.float64, order="C") |
nothing calls this directly
no test coverage detected