code: def test(self):
      # Return the y_test indices not X_test indices.
      # X_test indices are expanded indices for handling FH with gaps.
      # But if we return X_test indices, then we will get expanded test
      # indices even for univariate time series without exogenous variables
      # which would be confusing. Hence, we return y_test indices here and if
      # we want to get X_test indices, then we use self.X_test directly.
      # Refer:
      # https://github.com/sktime/sktime/issues/2598#issuecomment-1203308542
      # https://github.com/sktime/sktime/blob/4164639e1c521b112711c045d0f7e63013c1e4eb/sktime/forecasting/model_evaluation/_functions.py#L196
      return self.dataset.loc[self.idx[1], :]
  
file_path: pycaret/pycaret/internal/pycaret_experiment/ts_supervised_experiment.py
imports: import pandas
  from pycaret.internal.pycaret_experiment.supervised_experiment import _SupervisedExperiment
  from pycaret.utils.time_series.forecasting.pipeline import _pipeline_transform
label_desc: Use image node_id 8 for calling the _TSSupervisedExperiment obj's underlying member method code with example usage: obj.test() and returns: self