class_docstr: Base class for models which incorporate inFairness algorithms.
class_docstr_tok: ["Base","class","for","models","which","incorporate","inFairness","algorithms","."]
code: def _estimator_type(self):
      if hasattr(self, "regression_"):
          return "regressor" if self.regression_ else "classifier"
      elif self.regression != "auto":
          return "regressor" if self.regression else "classifier"
      else:
          raise NotFittedError(
              "regression is set to 'auto'. Call 'fit' with "
              "appropriate arguments or set regression manually."
          )
  
imports: from inFairness import fairalgo
  from sklearn.preprocessing import LabelBinarizer
  from sklearn.utils.multiclass import type_of_target
  from sklearn.exceptions import NotFittedError
  from skorch import NeuralNet
  from skorch.dataset import unpack_data, Dataset
  from skorch.utils import is_pandas_ndframe
label_desc: Use image node_id 2 for calling the InFairnessNet obj's underlying member method code with example usage: obj._estimator_type() and returns: unknown, unknown