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38 lines
890 B
Markdown
38 lines
890 B
Markdown
# KNearestNeighbors Classifier
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Classifier implementing the k-nearest neighbors algorithm.
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### Constructor Parameters
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* $k - number of nearest neighbors to scan (default: 3)
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* $distanceMetric - Distance class, default Euclidean (see Distance Metric documentation)
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```
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$classifier = new KNearestNeighbors($k=4);
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$classifier = new KNearestNeighbors($k=3, new Minkowski($lambda=4));
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```
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### Train
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To train a classifier simply provide train samples and labels (as `array`):
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```
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$samples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
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$labels = ['a', 'a', 'a', 'b', 'b', 'b'];
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$classifier = new KNearestNeighbors();
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$classifier->train($samples, $labels);
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```
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### Predict
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To predict sample class use `predict` method. You can provide one sample or array of samples:
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```
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$classifier->predict([3, 2]);
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// return 'b'
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$classifier->predict([[3, 2], [1, 5]]);
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// return ['b', 'a']
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```
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