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