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890 B
890 B
KNearestNeighbors Classifier
Classifier implementing the k-nearest neighbors algorithm.
Constructor Parameters
- $k - number of nearest neighbors to scan (default: 3)
- $distanceMetric - Distance class, default Euclidean (see Distance Metric 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
):
$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);
Predict
To predict sample class use 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']