Nearest Neighbor Classifier#

This topic demonstrates the process of creating an updatable empty k-nearest neighbor model using Core ML Tools.

Create the Classifier#

  1. Create the classifier and apply its properties:

    number_of_dimensions = 128
    from coremltools.models.nearest_neighbors import KNearestNeighborsClassifierBuilder
    builder = KNearestNeighborsClassifierBuilder(input_name='input',
    				 index_type='linear') = 'Core ML Tools Example'
    builder.license = 'MIT'
    builder.description = 'Classifies {} dimension vector based on 3 nearest neighbors'.format(number_of_dimensions)
    builder.spec.description.input[0].shortDescription = 'Input vector to classify'
    builder.spec.description.output[0].shortDescription = 'Predicted label. Defaults to \'defaultLabel\''
    builder.spec.description.output[1].shortDescription = 'Probabilities / score for each possible label.'
    builder.spec.description.trainingInput[0].shortDescription = 'Example input vector'
    builder.spec.description.trainingInput[1].shortDescription = 'Associated true label of each example vector'


    An empty knn model is updatable by default:

    # By default an empty knn model is updatable
  2. Confirm that the number of dimensions are set correctly:

    # Let's confirm the number of dimension is set correctly

Set the Number of Neighbors Value#

  1. Verify the current number of neighbors value:

    # Let's check what the value of 'numberOfNeighbors' is


    The number of neighbors is bounded by the default range:

    # The number of neighbors is bounded by the default range...
    (1, 1000)

    If you set the number of neighbors to a value outside of this default range, an ValueError will occur as shown in the Out tab:

    # If we try to set the number of neighbors to a value outside of this range
    builder.number_of_neighbors = 1001
    ValueError                                Traceback (most recent call last)
    <ipython-input-17-e8bea591e72c> in <module>
    	  1 # If we try to set the number of neighbors to a value outside of this range
    ----> 2 builder.number_of_neighbors = 1001
    ~/eng/sources/coreml/coremltools/coremltools/models/nearest_neighbors/ in number_of_neighbors(self, number_of_neighbors)
    	312                 self.spec.kNearestNeighborsClassifier.numberOfNeighbors.defaultValue = number_of_neighbors
    	313             else:
    --> 314                 raise ValueError('number_of_neighbors is not within range bounds')
    	315         else:
    	316             spec_values = self.spec.kNearestNeighborsClassifier.numberOfNeighbors.set.values
    ValueError: number_of_neighbors is not within range bounds
  2. Change the bounds for the number of neighbors. Individual values can be set for the numberOfNeighbors parameter:

    # Instead of a range, you can a set individual values that are valid for the numberOfNeighbors parameter.
    builder.set_number_of_neighbors_with_bounds(3, allowed_set={ 1, 3, 5 })
  3. Verify change using the number_of_neighbors_allowed_set() method.

    # Check out the results of the previous operation
    {1, 3, 5}
  4. The number of neighbors value can now be set without an error:

    # And now if you attempt to set it to an invalid value...
    builder.number_of_neighbors = 4
    ValueError                                Traceback (most recent call last)
    <ipython-input-20-98c77c72c722> in <module>
    	  1 # And now if you attempt to set it to an invalid value...
    ----> 2 builder.number_of_neighbors = 4
    ~/eng/sources/coreml/coremltools/coremltools/models/nearest_neighbors/ in number_of_neighbors(self, number_of_neighbors)
    	320                     self.spec.kNearestNeighborsClassifier.numberOfNeighbors.defaultValue = number_of_neighbors
    	321                     return
    --> 322             raise ValueError('number_of_neighbors is not an allowed value')
    	324     def set_number_of_neighbors_with_bounds(self, number_of_neighbors, allowed_range=None, allowed_set=None):
    ValueError: number_of_neighbors is not valid

If desired, you can revert back to a valid range:

# And of course you can go back to a valid range
builder.set_number_of_neighbors_with_bounds(3, allowed_range=(1, 30))

Set the Index Type#

  1. Verify the current index type:

    # Let's see what the index type is
  2. Set the index and leaf size:

    # Let's set the index to kd_tree with leaf size of 30
    builder.set_index_type('kd_tree', 30)
  3. Save the model:

    mlmodel_updatable_path = './UpdatableKNN.mlmodel'
    # Save the updated spec
    from coremltools.models import MLModel
    mlmodel_updatable = MLModel(builder.spec)