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https://github.com/Llewellynvdm/php-ml.git
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8f122fde90
* Models manager with save/restore capabilities * Refactoring dataset exceptions * Persistency layer docs * New tests for serializable estimators * ModelManager static methods to instance methods
94 lines
3.6 KiB
PHP
94 lines
3.6 KiB
PHP
<?php
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declare(strict_types=1);
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namespace tests\Regression;
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use Phpml\Regression\LeastSquares;
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use Phpml\ModelManager;
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class LeastSquaresTest extends \PHPUnit_Framework_TestCase
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{
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public function testPredictSingleFeatureSamples()
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{
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$delta = 0.01;
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//https://www.easycalculation.com/analytical/learn-least-square-regression.php
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$samples = [[60], [61], [62], [63], [65]];
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$targets = [3.1, 3.6, 3.8, 4, 4.1];
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$regression = new LeastSquares();
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$regression->train($samples, $targets);
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$this->assertEquals(4.06, $regression->predict([64]), '', $delta);
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//http://www.stat.wmich.edu/s216/book/node127.html
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$samples = [[9300], [10565], [15000], [15000], [17764], [57000], [65940], [73676], [77006], [93739], [146088], [153260]];
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$targets = [7100, 15500, 4400, 4400, 5900, 4600, 8800, 2000, 2750, 2550, 960, 1025];
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$regression = new LeastSquares();
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$regression->train($samples, $targets);
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$this->assertEquals(7659.35, $regression->predict([9300]), '', $delta);
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$this->assertEquals(5213.81, $regression->predict([57000]), '', $delta);
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$this->assertEquals(4188.13, $regression->predict([77006]), '', $delta);
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$this->assertEquals(7659.35, $regression->predict([9300]), '', $delta);
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$this->assertEquals(278.66, $regression->predict([153260]), '', $delta);
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}
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public function testPredictSingleFeatureSamplesWithMatrixTargets()
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{
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$delta = 0.01;
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//https://www.easycalculation.com/analytical/learn-least-square-regression.php
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$samples = [[60], [61], [62], [63], [65]];
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$targets = [[3.1], [3.6], [3.8], [4], [4.1]];
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$regression = new LeastSquares();
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$regression->train($samples, $targets);
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$this->assertEquals(4.06, $regression->predict([64]), '', $delta);
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}
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public function testPredictMultiFeaturesSamples()
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{
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$delta = 0.01;
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//http://www.stat.wmich.edu/s216/book/node129.html
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$samples = [[73676, 1996], [77006, 1998], [10565, 2000], [146088, 1995], [15000, 2001], [65940, 2000], [9300, 2000], [93739, 1996], [153260, 1994], [17764, 2002], [57000, 1998], [15000, 2000]];
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$targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400];
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$regression = new LeastSquares();
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$regression->train($samples, $targets);
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$this->assertEquals(-800614.957, $regression->getIntercept(), '', $delta);
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$this->assertEquals([-0.0327, 404.14], $regression->getCoefficients(), '', $delta);
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$this->assertEquals(4094.82, $regression->predict([60000, 1996]), '', $delta);
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$this->assertEquals(5711.40, $regression->predict([60000, 2000]), '', $delta);
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}
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public function testSaveAndRestore()
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{
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//https://www.easycalculation.com/analytical/learn-least-square-regression.php
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$samples = [[60], [61], [62], [63], [65]];
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$targets = [[3.1], [3.6], [3.8], [4], [4.1]];
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$regression = new LeastSquares();
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$regression->train($samples, $targets);
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//http://www.stat.wmich.edu/s216/book/node127.html
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$testSamples = [[9300], [10565], [15000]];
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$predicted = $regression->predict($testSamples);
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$filename = 'least-squares-test-'.rand(100, 999).'-'.uniqid();
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$filepath = tempnam(sys_get_temp_dir(), $filename);
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$modelManager = new ModelManager();
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$modelManager->saveToFile($regression, $filepath);
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$restoredRegression = $modelManager->restoreFromFile($filepath);
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$this->assertEquals($regression, $restoredRegression);
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$this->assertEquals($predicted, $restoredRegression->predict($testSamples));
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}
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}
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