class_docstr: A classifier.
class_docstr_tok: ["A","classifier","."]
docstr: Predict the label of a set of features `x`.
  
  Parameters
  ----------
  x
      A dictionary of features.
  
  Returns
  -------
  The predicted label.
docstr_tok: ["Predict","the","label","of","a","set","of","features","`","x","`",".","Parameters","--","--","--","--","--","x","A","dictionary","of","features",".","Returns","--","--","--","-","The","predicted","label","."]
code: def predict_one(
      self, x: dict, **kwargs
  ) -> base.typing.ClfTarget | None:
      """Predict the label of a set of features `x`.
  
      Parameters
      ----------
      x
          A dictionary of features.
  
      Returns
      -------
      The predicted label.
  
      """
  
      # The following code acts as a default for each classifier, and may be overridden on an
      # individual basis.
      y_pred = self.predict_proba_one(x, **kwargs)
      if y_pred:
          return max(y_pred, key=y_pred.get)  # type: ignore
      return None
  
file_path: river/river/base/classifier.py
imports: from __future__ import annotations
  import abc
  import typing
  from river import base
  from .None import estimator
label_desc: Use image node_id 3 for calling the Classifier obj's underlying member method code with example usage: obj.predict_one(x) and returns: None, max