code: def predict(self, measurement, output_format='array'):
          
          scores = np.array([])
          for obs in self.observations:
              knn = self.__get_knn_by_observation(obs)
              p, ids = self.__get_features_for_observation(data_frame=measurement, observation=obs,
                                                           skip_id=3497, last_column_is_id=True)
  
              score = knn.predict(pd.DataFrame(p).T)
              scores = np.append(scores, score, axis=0)
  
          if output_format == 'array':
              return scores.astype(int)
          else:
              return np.array_str(scores.astype(int))
docs: Method to predict the class labels for the provided data
  
              :param measurement: the point to classify
              :type measurement: pandas.DataFrame
              :param output_format: the format to return the scores ('array' or 'str')
              :type output_format: string
              :return prediction: the prediction for a given test/point
              :rtype prediction: np.array