docstr: Returns a list of feature names, ordered by their indices.
  
  If one-of-K coding is applied to categorical features, this will
  include the constructed feature names but not the original ones.
docstr_tok: ["Returns","a","list","of","feature","names",",","ordered","by","their","indices",".","If","one-of-K","coding","is","applied","to","categorical","features",",","this","will","include","the","constructed","feature","names","but","not","the","original","ones","."]
code: def get_feature_names(self):
      """Returns a list of feature names, ordered by their indices.
  
      If one-of-K coding is applied to categorical features, this will
      include the constructed feature names but not the original ones.
      """
      return self.feature_names_
  
imports: from array import array
  import numbers
  from operator import itemgetter
  import numpy
  import pandas
  import scipy.sparse
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.externals import six
  from auto_ml.utils import CustomLabelEncoder
label_desc: Use image node_id 7 for calling the DataFrameVectorizer obj's underlying member method code with example usage: obj.get_feature_names() and returns: self