code: def predict(self, features):
          
          if not self.fitted_pipeline_:
              raise RuntimeError('A pipeline has not yet been optimized. Please call fit() first.')
  
          features = self._check_dataset(features, target=None, sample_weight=None)
  
          return self.fitted_pipeline_.predict(features)
docs: Use the optimized pipeline to predict the target for a feature set.
  
          Parameters
          ----------
          features: array-like {n_samples, n_features}
              Feature matrix
  
          Returns
          ----------
          array-like: {n_samples}
              Predicted target for the samples in the feature matrix