docstr: Unscale the time series dataset's feature column and target column.
  
  :return: the tsdataset instance.
code: def unscale(self):
      """
      Unscale the time series dataset's feature column and target column.
  
      :return: the tsdataset instance.
      """
      feature_col = self.feature_col
      if self.roll_additional_feature:
          feature_col = []
          for feature in self.feature_col:
              if feature not in self.roll_additional_feature:
                  feature_col.append(feature)
      self.df[
          self.target_col + feature_col
      ] = self.scaler.inverse_transform(
          self.df[self.target_col + feature_col]
      )
      return self
  
imports: import pandas
  import numpy
  import functools
  import logging
  from bigdl.chronos.data.utils.feature import generate_dt_features, generate_global_features
  from bigdl.chronos.data.utils.impute import impute_timeseries_dataframe
  from bigdl.chronos.data.utils.deduplicate import deduplicate_timeseries_dataframe
  from bigdl.chronos.data.utils.roll import roll_timeseries_dataframe
  from bigdl.chronos.data.utils.time_feature import time_features, gen_time_enc_arr
  from bigdl.chronos.data.utils.scale import unscale_timeseries_numpy, scale_timeseries_numpy
  from bigdl.chronos.data.utils.resample import resample_timeseries_dataframe
  from bigdl.chronos.data.utils.split import split_timeseries_dataframe
  from bigdl.chronos.data.utils.cycle_detection import cycle_length_est
  from bigdl.chronos.data.utils.quality_inspection import quality_check_timeseries_dataframe, _abnormal_value_repair
  from bigdl.chronos.data.utils.utils import _to_list, _check_type, _check_col_within, _check_col_no_na, _check_is_aligned, _check_dt_is_sorted
label_desc: Use image node_id 18 for calling the TSDataset obj's underlying member method code with example usage: obj.unscale() and returns: self