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https://github.com/Llewellynvdm/php-ml.git
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61 lines
2.2 KiB
PHP
61 lines
2.2 KiB
PHP
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<?php
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declare(strict_types=1);
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namespace tests\Classification;
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use Phpml\Classification\DecisionTree;
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class DecisionTreeTest extends \PHPUnit_Framework_TestCase
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{
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public $data = [
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['sunny', 85, 85, 'false', 'Dont_play' ],
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['sunny', 80, 90, 'true', 'Dont_play' ],
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['overcast', 83, 78, 'false', 'Play' ],
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['rain', 70, 96, 'false', 'Play' ],
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['rain', 68, 80, 'false', 'Play' ],
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['rain', 65, 70, 'true', 'Dont_play' ],
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['overcast', 64, 65, 'true', 'Play' ],
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['sunny', 72, 95, 'false', 'Dont_play' ],
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['sunny', 69, 70, 'false', 'Play' ],
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['rain', 75, 80, 'false', 'Play' ],
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['sunny', 75, 70, 'true', 'Play' ],
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['overcast', 72, 90, 'true', 'Play' ],
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['overcast', 81, 75, 'false', 'Play' ],
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['rain', 71, 80, 'true', 'Dont_play' ]
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];
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public function getData()
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{
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static $data = null, $targets = null;
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if ($data == null) {
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$data = $this->data;
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$targets = array_column($data, 4);
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array_walk($data, function (&$v) {
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array_splice($v, 4, 1);
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});
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}
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return [$data, $targets];
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}
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public function testPredictSingleSample()
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{
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list($data, $targets) = $this->getData();
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$classifier = new DecisionTree(5);
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$classifier->train($data, $targets);
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$this->assertEquals('Dont_play', $classifier->predict(['sunny', 78, 72, 'false']));
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$this->assertEquals('Play', $classifier->predict(['overcast', 60, 60, 'false']));
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$this->assertEquals('Dont_play', $classifier->predict(['rain', 60, 60, 'true']));
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return $classifier;
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}
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public function testTreeDepth()
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{
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list($data, $targets) = $this->getData();
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$classifier = new DecisionTree(5);
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$classifier->train($data, $targets);
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$this->assertTrue(5 >= $classifier->actualDepth);
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}
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}
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