# KNN Classifier
This package provides a utility for creating a classifier using the
[K-Nearest Neighbors](https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm)
algorithm.
This package is different from the other packages in this repository in that it
doesn't provide a model with weights, but rather a utility for constructing a
KNN model using activations from another model or any other tensors you can
associate with a class/label.
You can see example code [here](https://github.com/tensorflow/tfjs-models/tree/master/knn-classifier/demo).
## Usage example
##### via Script Tag
```html
```
###### via NPM
```js
import * as tf from '@tensorflow/tfjs';
import * as mobilenetModule from '@tensorflow-models/mobilenet';
import * as knnClassifier from '@tensorflow-models/knn-classifier';
// Create the classifier.
const classifier = knnClassifier.create();
// Load mobilenet.
const mobilenet = await mobilenetModule.load();
// Add MobileNet activations to the model repeatedly for all classes.
const img0 = tf.browser.fromPixels(document.getElementById('class0'));
const logits0 = mobilenet.infer(img0, 'conv_preds');
classifier.addExample(logits0, 0);
const img1 = tf.browser.fromPixels(document.getElementById('class1'));
const logits1 = mobilenet.infer(img1, 'conv_preds');
classifier.addExample(logits1, 1);
// Make a prediction.
const x = tf.browser.fromPixels(document.getElementById('test'));
const xlogits = mobilenet.infer(x, 'conv_preds');
console.log('Predictions:');
console.log(classifier.predictClass(xlogits));
```
## API
#### Creating a classifier
`knnClassifier` is the module name, which is automatically included when you use
the