Nearest Neighbor Classifier — Guide to Core ML Tools (original) (raw)

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',
    output_name='output',
    number_of_dimensions=number_of_dimensions,
    default_class_label='defaultLabel',
    number_of_neighbors=3,
    weighting_scheme='inverse_distance',
    index_type='linear')

builder.author = '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'
Note
An empty knn model is updatable by default:

By default an empty knn model is updatable

builder.is_updatable 2. Confirm that the number of dimensions are set correctly:

Let's confirm the number of dimension is set correctly

builder.number_of_dimensions

Set the Number of Neighbors Value#

  1. Verify the current number of neighbors value:

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

builder.number_of_neighbors
Note
The number of neighbors is bounded by the default range:
# The number of neighbors is bounded by the default range...
builder.number_of_neighbors_allowed_range()
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)
in
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/builder.py 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
builder.number_of_neighbors_allowed_set() 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)
in
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/builder.py 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')
323
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

builder.index_type 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)
builder.index_type 3. Save the model:
mlmodel_updatable_path = './UpdatableKNN.mlmodel'

Save the updated spec

from coremltools.models import MLModel
mlmodel_updatable = MLModel(builder.spec)
mlmodel_updatable.save(mlmodel_updatable_path)