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: Get the leaf size for the KNearestNeighborsClassifier
  :return: the leaf size
docstr_tok: ["Get","the","leaf","size","for","the","KNearestNeighborsClassifier",":","return",":","the","leaf","size"]
code: def leaf_size(self):
      """
      Get the leaf size for the KNearestNeighborsClassifier
      :return: the leaf size
      """
      return (
          self.spec.kNearestNeighborsClassifier.nearestNeighborsIndex.singleKdTreeIndex.leafSize
      )
  
imports: from ...proto import FeatureTypes_pb2
  from ..None import datatypes
  import coremltools
  import numpy
  import six
label_desc: Use image node_id 14 for calling the KNearestNeighborsClassifierBuilder obj's underlying member method code with example usage: obj.leaf_size() and returns: self