class_docstr: Abstract class for confusion matrix
  
  You shouldn't instantiate this class.
  You might instantiate ConfusionMatrix or BinaryConfusionMatrix classes
class_docstr_tok: ["Abstract","class","for","confusion","matrix","You","should","n't","instantiate","this","class",".","You","might","instantiate","ConfusionMatrix","or","BinaryConfusionMatrix","classes"]
docstr: Enlarges confusion matrix with new classes
  It should add empty rows and columns
docstr_tok: ["Enlarges","confusion","matrix","with","new","classes","It","should","add","empty","rows","and","columns"]
code: def enlarge(self, select):
      """
      Enlarges confusion matrix with new classes
      It should add empty rows and columns
      """
      if not isinstance(select, collections.Iterable):
          idx_new_cls = pd.Index([select])
      else:
          idx_new_cls = pd.Index(select)
      new_idx = self._df_confusion.index | idx_new_cls
      new_idx.name = self.true_name
      new_col = self._df_confusion.columns | idx_new_cls
      new_col.name = self.pred_name
      print(new_col)
      self._df_confusion = self._df_confusion.loc[:, new_col]
  
imports: import numpy
  import pandas
  import collections
  import pandas_ml
  from pandas_ml.confusion_matrix.stats import binom_interval, class_agreement, prop_test
label_desc: Use image node_id 20 for calling the ConfusionMatrixAbstract obj's underlying member method code with example usage: obj.enlarge(select) without return types