class_docstr: Dummy classifier which returns the last class seen.
  
  The predict_one method will output the last class seen whilst predict_proba_one will
  return 1 for the last class seen and 0 for the others.
  
  Attributes
  ----------
  last_class
      The last class seen.
  classes
      The set of classes seen.
  
  Examples
  --------
  
  Taken from example 2.1 from
  [this page](https://www.cms.waikato.ac.nz/~abifet/book/chapter_2.html).
  
  >>> import pprint
  >>> from river import dummy
  
  >>> sentences = [
  ...     ('glad happy glad', '+'),
  ...     ('glad glad joyful', '+'),
  ...     ('glad pleasant', '+'),
  ...     ('miserable sad glad', '−')
  ... ]
  
  >>> model = dummy.NoChangeClassifier()
  
  >>> for sentence, label in sentences:
  ...     model.learn_one(sentence, label)
  
  >>> new_sentence = 'glad sad miserable pleasant glad'
  >>> model.predict_one(new_sentence)
  '−'
  
  >>> pprint.pprint(model.predict_proba_one(new_sentence))
  {'+': 0, '−': 1}
code: def __init__(self):
      self.last_class = None
      self.classes = set()
  
imports: from __future__ import annotations
  import collections
  from river import base, stats
label_desc: Use image node_id 1 to create a new NoChangeClassifier object from inherited base classes: base with example: obj = NoChangeClassifier()