php-ml/tests/Phpml/Classification/SVCTest.php
2016-05-07 22:17:12 +02:00

46 lines
1.6 KiB
PHP

<?php
declare (strict_types = 1);
namespace tests\Classification;
use Phpml\Classification\SVC;
use Phpml\SupportVectorMachine\Kernel;
class SVCTest extends \PHPUnit_Framework_TestCase
{
public function testPredictSingleSampleWithLinearKernel()
{
$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);
$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 testPredictArrayOfSamplesWithLinearKernel()
{
$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);
$this->assertEquals($testLabels, $predictions);
}
}