code: def y_transformed(self):
      # Use fully trained pipeline to get the requested data
      # In time series, the order of arguments and returns may be reversed.
      return _pipeline_transform(
          pipeline=self.pipeline_fully_trained, y=self.y, X=self.X
      )[0]
  
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 10 for calling the _TSSupervisedExperiment obj's underlying member method code with example usage: obj.y_transformed() and returns: _pipeline_transform