php-ml/tests/Classification/SVCTest.php
2018-10-28 07:44:52 +01:00

89 lines
3.1 KiB
PHP

<?php
declare(strict_types=1);
namespace Phpml\Tests\Classification;
use Phpml\Classification\SVC;
use Phpml\ModelManager;
use Phpml\SupportVectorMachine\Kernel;
use PHPUnit\Framework\TestCase;
class SVCTest extends TestCase
{
public function testPredictSingleSampleWithLinearKernel(): void
{
$samples = [[1, 3], [1, 4], [2, 4], [3, 1], [4, 1], [4, 2]];
$labels = ['a', 'a', 'a', 'b', 'b', 'b'];
$classifier = new SVC(Kernel::LINEAR, $cost = 1000);
$classifier->train($samples, $labels);
self::assertEquals('b', $classifier->predict([3, 2]));
self::assertEquals('b', $classifier->predict([5, 1]));
self::assertEquals('b', $classifier->predict([4, 3]));
self::assertEquals('b', $classifier->predict([4, -5]));
self::assertEquals('a', $classifier->predict([2, 3]));
self::assertEquals('a', $classifier->predict([1, 2]));
self::assertEquals('a', $classifier->predict([1, 5]));
self::assertEquals('a', $classifier->predict([3, 10]));
}
public function testPredictArrayOfSamplesWithLinearKernel(): void
{
$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 SVC(Kernel::LINEAR, $cost = 1000);
$classifier->train($trainSamples, $trainLabels);
$predictions = $classifier->predict($testSamples);
self::assertEquals($testLabels, $predictions);
}
public function testSaveAndRestore(): void
{
$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]];
$testLabels = ['b', 'b', 'b'];
$classifier = new SVC(Kernel::LINEAR, $cost = 1000);
$classifier->train($trainSamples, $trainLabels);
$predicted = $classifier->predict($testSamples);
$filepath = (string) tempnam(sys_get_temp_dir(), uniqid('svc-test', true));
$modelManager = new ModelManager();
$modelManager->saveToFile($classifier, $filepath);
$restoredClassifier = $modelManager->restoreFromFile($filepath);
self::assertEquals($classifier, $restoredClassifier);
self::assertEquals($predicted, $restoredClassifier->predict($testSamples));
self::assertEquals($predicted, $testLabels);
}
public function testWithNonDotDecimalLocale(): void
{
$currentLocale = setlocale(LC_NUMERIC, '0');
setlocale(LC_NUMERIC, 'pl_PL.utf8');
$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]];
$testLabels = ['b', 'b', 'b'];
$classifier = new SVC(Kernel::LINEAR, $cost = 1000);
$classifier->train($trainSamples, $trainLabels);
self::assertEquals($classifier->predict($testSamples), $testLabels);
setlocale(LC_NUMERIC, (string) $currentLocale);
}
}