php-ml/tests/Phpml/Classification/KNearestNeighborsTest.php
2017-02-03 12:58:25 +01:00

86 lines
3.2 KiB
PHP

<?php
declare(strict_types=1);
namespace tests\Classification;
use Phpml\Classification\KNearestNeighbors;
use Phpml\Math\Distance\Chebyshev;
use Phpml\ModelManager;
use PHPUnit\Framework\TestCase;
class KNearestNeighborsTest extends TestCase
{
public function testPredictSingleSampleWithDefaultK()
{
$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);
$this->assertEquals('b', $classifier->predict([3, 2]));
$this->assertEquals('b', $classifier->predict([5, 1]));
$this->assertEquals('b', $classifier->predict([4, 3]));
$this->assertEquals('b', $classifier->predict([4, -5]));
$this->assertEquals('a', $classifier->predict([2, 3]));
$this->assertEquals('a', $classifier->predict([1, 2]));
$this->assertEquals('a', $classifier->predict([1, 5]));
$this->assertEquals('a', $classifier->predict([3, 10]));
}
public function testPredictArrayOfSamples()
{
$trainSamples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
$trainLabels = ['a', 'a', 'a', 'b', 'b', 'b'];
$testSamples = [[3, 2], [5, 1], [4, 3], [4, -5], [2, 3], [1, 2], [1, 5], [3, 10]];
$testLabels = ['b', 'b', 'b', 'b', 'a', 'a', 'a', 'a'];
$classifier = new KNearestNeighbors();
$classifier->train($trainSamples, $trainLabels);
$predicted = $classifier->predict($testSamples);
$this->assertEquals($testLabels, $predicted);
}
public function testPredictArrayOfSamplesUsingChebyshevDistanceMetric()
{
$trainSamples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
$trainLabels = ['a', 'a', 'a', 'b', 'b', 'b'];
$testSamples = [[3, 2], [5, 1], [4, 3], [4, -5], [2, 3], [1, 2], [1, 5], [3, 10]];
$testLabels = ['b', 'b', 'b', 'b', 'a', 'a', 'a', 'a'];
$classifier = new KNearestNeighbors(3, new Chebyshev());
$classifier->train($trainSamples, $trainLabels);
$predicted = $classifier->predict($testSamples);
$this->assertEquals($testLabels, $predicted);
}
public function testSaveAndRestore()
{
$trainSamples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
$trainLabels = ['a', 'a', 'a', 'b', 'b', 'b'];
$testSamples = [[3, 2], [5, 1], [4, 3], [4, -5], [2, 3], [1, 2], [1, 5], [3, 10]];
$testLabels = ['b', 'b', 'b', 'b', 'a', 'a', 'a', 'a'];
// Using non-default constructor parameters to check that their values are restored.
$classifier = new KNearestNeighbors(3, new Chebyshev());
$classifier->train($trainSamples, $trainLabels);
$predicted = $classifier->predict($testSamples);
$filename = 'knearest-neighbors-test-'.rand(100, 999).'-'.uniqid();
$filepath = tempnam(sys_get_temp_dir(), $filename);
$modelManager = new ModelManager();
$modelManager->saveToFile($classifier, $filepath);
$restoredClassifier = $modelManager->restoreFromFile($filepath);
$this->assertEquals($classifier, $restoredClassifier);
$this->assertEquals($predicted, $restoredClassifier->predict($testSamples));
}
}