class_docstr: KNearestNeighborsClassifierBuilder class to construct a CoreML KNearestNeighborsClassifier specification.
  
  Please see the Core ML Nearest Neighbors protobuf message for more information
  on KNearestNeighborsClassifier parameters.
  
  Examples
  --------
  .. sourcecode:: python
  
      from coremltools.models.nearest_neighbors import KNearestNeighborsClassifierBuilder
      from coremltools.models.utils import save_spec
  
      # Create a KNearestNeighborsClassifier model that takes 4-dimensional input data and outputs a string label.
      >>> builder = KNearestNeighborsClassifierBuilder(input_name='input',
      ...                                              output_name='output',
      ...                                              number_of_dimensions=4,
      ...                                              default_class_label='default_label')
  
      # save the spec by the builder
      >>> save_spec(builder.spec, 'knnclassifier.mlmodel')
  
  See Also
  --------
  MLModel, save_spec
docstr: Add an author for the KNearestNeighborsClassifier model
  :param author: the author
  :return: None
docstr_tok: ["Add","an","author","for","the","KNearestNeighborsClassifier","model",":","param","author",":","the","author",":","return",":","None"]
code: def author(self, author):
      """
      Add an author for the KNearestNeighborsClassifier model
      :param author: the author
      :return: None
      """
      self.spec.description.metadata.author = author
  
imports: from ...proto import FeatureTypes_pb2
  from ..None import datatypes
  import coremltools
  import numpy
  import six
label_desc: Use image node_id 3 for calling the KNearestNeighborsClassifierBuilder obj's underlying member method code with example usage: obj.author(author) without return types