class_docstr: Base class for all imputers.
  
  It adds automatically support for `add_indicator`.
class_docstr_tok: ["Base","class","for","all","imputers",".","It","adds","automatically","support","for","`","add_indicator","`","."]
code: def _concatenate_indicator_feature_names_out(
      self, names, input_features
  ):
      if not self.add_indicator:
          return names
  
      indicator_names = self.indicator_.get_feature_names_out(
          input_features
      )
      return np.concatenate([names, indicator_names])
  
imports: import numbers
  import warnings
  from collections import Counter
  import numpy
  import numpy.ma
  from scipy import sparse
  from ..base import BaseEstimator, TransformerMixin, _fit_context
  from ..utils import _is_pandas_na, is_scalar_nan
  from ..utils._mask import _get_mask
  from ..utils._param_validation import MissingValues, StrOptions
  from ..utils.fixes import _mode
  from ..utils.sparsefuncs import _get_median
  from ..utils.validation import FLOAT_DTYPES, _check_feature_names_in, check_is_fitted
label_desc: Use image node_id 5 for calling the _BaseImputer obj's underlying member method code with example usage: obj._concatenate_indicator_feature_names_out(names, input_features) and returns: np, names