php-ml/docs/machine-learning/classification/k-nearest-neighbors.md

KNearestNeighbors Classifier

Classifier implementing the k-nearest neighbors algorithm.

Constructor Parameters

• $k - number of nearest neighbors to scan (default: 3)
• $distanceMetric - Distance object, default Euclidean (see distance documentation)

$classifier = new KNearestNeighbors($k=4);
$classifier = new KNearestNeighbors($k=3, new Minkowski($lambda=4));

Train

To train a classifier, simply provide train samples and labels (as array). Example:

$samples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
$labels = ['a', 'a', 'a', 'b', 'b', 'b'];

$classifier = new KNearestNeighbors();
$classifier->train($samples, $labels);

You can train the classifier using multiple data sets, predictions will be based on all the training data.

Predict

To predict sample label use the predict method. You can provide one sample or array of samples:

$classifier->predict([3, 2]);
// return 'b'

$classifier->predict([[3, 2], [1, 5]]);
// return ['b', 'a']