code: def get_feature_names_out(self, input_features=None):
      feature_names = []
      for col in self.columns_:
          enc = self.encoders_[col]
          feature_names.extend(enc.get_feature_names_out([str(col)]))
          feature_names.append("{}_dabl_continuous".format(col))
      return np.array(feature_names)
  
imports: from importlib.metadata import version
  from joblib import hash
  import warnings
  from warnings import warn
  import numpy
  import pandas
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.compose import make_column_transformer, ColumnTransformer
  from sklearn.impute import SimpleImputer
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import OneHotEncoder, StandardScaler
  from sklearn.utils.validation import check_is_fitted
label_desc: Use image node_id 3 for calling the DirtyFloatCleaner obj's underlying member method code with example usage: obj.get_feature_names_out(input_features) and returns: np