class_docstr: Base adapter class for tsfresh transformations.
class_docstr_tok: ["Base","adapter","class","for","tsfresh","transformations","."]
code: def __init__(
      self,
      default_fc_parameters=None,
      kind_to_fc_parameters=None,
      chunksize=None,
      n_jobs=1,
      show_warnings=True,
      disable_progressbar=False,
      impute_function=None,
      profiling=None,
      profiling_filename=None,
      profiling_sorting=None,
      distributor=None,
  ):
      self.default_fc_parameters = default_fc_parameters
      self.kind_to_fc_parameters = kind_to_fc_parameters
      self.n_jobs = n_jobs
      self.chunksize = chunksize
      self.show_warnings = show_warnings
      self.disable_progressbar = disable_progressbar
      self.impute_function = impute_function
      self.profiling = profiling
      self.profiling_sorting = profiling_sorting
      self.profiling_filename = profiling_filename
      self.distributor = distributor
  
      super().__init__()
  
      # _get_extraction_params should be after the init because this imports tsfresh
      # and the init checks for python version and tsfresh being present
      self.default_fc_parameters_ = self._get_extraction_params()
  
file_path: sktime/sktime/transformations/panel/tsfresh.py
imports: from sktime.transformations.base import BaseTransformer
  from sktime.utils.validation import check_n_jobs
label_desc: Use image node_id 1 to create a new _TSFreshFeatureExtractor object from inherited base classes: BaseTransformer with example: obj = _TSFreshFeatureExtractor(default_fc_parameters, kind_to_fc_parameters, chunksize, n_jobs, show_warnings, disable_progressbar, impute_function, profiling, profiling_filename, profiling_sorting, distributor)