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

83 lines
2.8 KiB
PHP

<?php
declare(strict_types=1);
namespace Phpml\Tests\Classification\Ensemble;
use Phpml\Classification\Ensemble\AdaBoost;
use Phpml\Exception\InvalidArgumentException;
use Phpml\ModelManager;
use PHPUnit\Framework\TestCase;
class AdaBoostTest extends TestCase
{
public function testTrainThrowWhenMultiClassTargetGiven(): void
{
$samples = [
[0, 0],
[0.5, 0.5],
[1, 1],
];
$targets = [
0,
1,
2,
];
$classifier = new AdaBoost();
$this->expectException(InvalidArgumentException::class);
$classifier->train($samples, $targets);
}
public function testPredictSingleSample(): void
{
// AND problem
$samples = [[0.1, 0.3], [1, 0], [0, 1], [1, 1], [0.9, 0.8], [1.1, 1.1]];
$targets = [0, 0, 0, 1, 1, 1];
$classifier = new AdaBoost();
$classifier->train($samples, $targets);
self::assertEquals(0, $classifier->predict([0.1, 0.2]));
self::assertEquals(0, $classifier->predict([0.1, 0.99]));
self::assertEquals(1, $classifier->predict([1.1, 0.8]));
// OR problem
$samples = [[0, 0], [0.1, 0.2], [0.2, 0.1], [1, 0], [0, 1], [1, 1]];
$targets = [0, 0, 0, 1, 1, 1];
$classifier = new AdaBoost();
$classifier->train($samples, $targets);
self::assertEquals(0, $classifier->predict([0.1, 0.2]));
self::assertEquals(1, $classifier->predict([0.1, 0.99]));
self::assertEquals(1, $classifier->predict([1.1, 0.8]));
// XOR problem
$samples = [[0.1, 0.2], [1., 1.], [0.9, 0.8], [0., 1.], [1., 0.], [0.2, 0.8]];
$targets = [0, 0, 0, 1, 1, 1];
$classifier = new AdaBoost(5);
$classifier->train($samples, $targets);
self::assertEquals(0, $classifier->predict([0.1, 0.1]));
self::assertEquals(1, $classifier->predict([0, 0.999]));
self::assertEquals(0, $classifier->predict([1.1, 0.8]));
}
public function testSaveAndRestore(): void
{
// Instantinate new Percetron trained for OR problem
$samples = [[0, 0], [1, 0], [0, 1], [1, 1]];
$targets = [0, 1, 1, 1];
$classifier = new AdaBoost();
$classifier->train($samples, $targets);
$testSamples = [[0, 1], [1, 1], [0.2, 0.1]];
$predicted = $classifier->predict($testSamples);
$filename = 'adaboost-test-'.random_int(100, 999).'-'.uniqid('', false);
$filepath = (string) tempnam(sys_get_temp_dir(), $filename);
$modelManager = new ModelManager();
$modelManager->saveToFile($classifier, $filepath);
$restoredClassifier = $modelManager->restoreFromFile($filepath);
self::assertEquals($classifier, $restoredClassifier);
self::assertEquals($predicted, $restoredClassifier->predict($testSamples));
}
}