php-ml/tests/Phpml/Classification/Linear/AdalineTest.php
Mustafa Karabulut cf222bcce4 Linear classifiers: Perceptron, Adaline, DecisionStump (#50)
* Linear classifiers

* Code formatting to PSR-2

* Added basic test cases for linear classifiers
2017-02-16 23:23:55 +01:00

56 lines
1.9 KiB
PHP

<?php
declare(strict_types=1);
namespace tests\Classification\Linear;
use Phpml\Classification\Linear\Adaline;
use Phpml\ModelManager;
use PHPUnit\Framework\TestCase;
class AdalineTest extends TestCase
{
public function testPredictSingleSample()
{
// AND problem
$samples = [[0, 0], [1, 0], [0, 1], [1, 1]];
$targets = [0, 0, 0, 1];
$classifier = new Adaline();
$classifier->train($samples, $targets);
$this->assertEquals(0, $classifier->predict([0.1, 0.2]));
$this->assertEquals(0, $classifier->predict([0.1, 0.99]));
$this->assertEquals(1, $classifier->predict([1.1, 0.8]));
// OR problem
$samples = [[0, 0], [1, 0], [0, 1], [1, 1]];
$targets = [0, 1, 1, 1];
$classifier = new Adaline();
$classifier->train($samples, $targets);
$this->assertEquals(0, $classifier->predict([0.1, 0.2]));
$this->assertEquals(1, $classifier->predict([0.1, 0.99]));
$this->assertEquals(1, $classifier->predict([1.1, 0.8]));
return $classifier;
}
public function testSaveAndRestore()
{
// Instantinate new Percetron trained for OR problem
$samples = [[0, 0], [1, 0], [0, 1], [1, 1]];
$targets = [0, 1, 1, 1];
$classifier = new Adaline();
$classifier->train($samples, $targets);
$testSamples = [[0, 1], [1, 1], [0.2, 0.1]];
$predicted = $classifier->predict($testSamples);
$filename = 'adaline-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));
}
}