def _convert_instances_(self, X, Y): logger.debug("Creating the Dataset") x1, x2, garbage, y_double, garbage = generate_complete_pairwise_dataset( X, Y) del garbage logger.debug("Finished the Dataset instances {}".format(x1.shape[0])) return x1, x2, y_double
def _convert_instances_(self, X, Y): self.logger.debug('Creating the Dataset') garbage, garbage, x_train, garbage, y_single = generate_complete_pairwise_dataset( X, Y) del garbage assert x_train.shape[1] == self.n_object_features self.logger.debug('Finished the Dataset with instances {}'.format( x_train.shape[0])) return x_train, y_single
def _convert_instances_(self, X, Y): self.logger.debug("Creating the Dataset") x1, x2, garbage, garbage, y_single = generate_complete_pairwise_dataset(X, Y) del garbage if x1.shape[0] > self.threshold_instances: indices = self.random_state.choice( x1.shape[0], self.threshold_instances, replace=False ) x1 = x1[indices, :] x2 = x2[indices, :] y_single = y_single[indices] self.logger.debug("Finished the Dataset instances {}".format(x1.shape[0])) return x1, x2, y_single