php-ml/tests/Phpml/Regression/LeastSquaresTest.php
David Monllaó 8f122fde90 Persistence class to save and restore models (#37)
* Models manager with save/restore capabilities

* Refactoring dataset exceptions

* Persistency layer docs

* New tests for serializable estimators

* ModelManager static methods to instance methods
2017-02-02 09:03:09 +01:00

94 lines
3.6 KiB
PHP

<?php
declare(strict_types=1);
namespace tests\Regression;
use Phpml\Regression\LeastSquares;
use Phpml\ModelManager;
class LeastSquaresTest extends \PHPUnit_Framework_TestCase
{
public function testPredictSingleFeatureSamples()
{
$delta = 0.01;
//https://www.easycalculation.com/analytical/learn-least-square-regression.php
$samples = [[60], [61], [62], [63], [65]];
$targets = [3.1, 3.6, 3.8, 4, 4.1];
$regression = new LeastSquares();
$regression->train($samples, $targets);
$this->assertEquals(4.06, $regression->predict([64]), '', $delta);
//http://www.stat.wmich.edu/s216/book/node127.html
$samples = [[9300], [10565], [15000], [15000], [17764], [57000], [65940], [73676], [77006], [93739], [146088], [153260]];
$targets = [7100, 15500, 4400, 4400, 5900, 4600, 8800, 2000, 2750, 2550, 960, 1025];
$regression = new LeastSquares();
$regression->train($samples, $targets);
$this->assertEquals(7659.35, $regression->predict([9300]), '', $delta);
$this->assertEquals(5213.81, $regression->predict([57000]), '', $delta);
$this->assertEquals(4188.13, $regression->predict([77006]), '', $delta);
$this->assertEquals(7659.35, $regression->predict([9300]), '', $delta);
$this->assertEquals(278.66, $regression->predict([153260]), '', $delta);
}
public function testPredictSingleFeatureSamplesWithMatrixTargets()
{
$delta = 0.01;
//https://www.easycalculation.com/analytical/learn-least-square-regression.php
$samples = [[60], [61], [62], [63], [65]];
$targets = [[3.1], [3.6], [3.8], [4], [4.1]];
$regression = new LeastSquares();
$regression->train($samples, $targets);
$this->assertEquals(4.06, $regression->predict([64]), '', $delta);
}
public function testPredictMultiFeaturesSamples()
{
$delta = 0.01;
//http://www.stat.wmich.edu/s216/book/node129.html
$samples = [[73676, 1996], [77006, 1998], [10565, 2000], [146088, 1995], [15000, 2001], [65940, 2000], [9300, 2000], [93739, 1996], [153260, 1994], [17764, 2002], [57000, 1998], [15000, 2000]];
$targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400];
$regression = new LeastSquares();
$regression->train($samples, $targets);
$this->assertEquals(-800614.957, $regression->getIntercept(), '', $delta);
$this->assertEquals([-0.0327, 404.14], $regression->getCoefficients(), '', $delta);
$this->assertEquals(4094.82, $regression->predict([60000, 1996]), '', $delta);
$this->assertEquals(5711.40, $regression->predict([60000, 2000]), '', $delta);
}
public function testSaveAndRestore()
{
//https://www.easycalculation.com/analytical/learn-least-square-regression.php
$samples = [[60], [61], [62], [63], [65]];
$targets = [[3.1], [3.6], [3.8], [4], [4.1]];
$regression = new LeastSquares();
$regression->train($samples, $targets);
//http://www.stat.wmich.edu/s216/book/node127.html
$testSamples = [[9300], [10565], [15000]];
$predicted = $regression->predict($testSamples);
$filename = 'least-squares-test-'.rand(100, 999).'-'.uniqid();
$filepath = tempnam(sys_get_temp_dir(), $filename);
$modelManager = new ModelManager();
$modelManager->saveToFile($regression, $filepath);
$restoredRegression = $modelManager->restoreFromFile($filepath);
$this->assertEquals($regression, $restoredRegression);
$this->assertEquals($predicted, $restoredRegression->predict($testSamples));
}
}