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* tests: update to PHPUnit 6.0 with rector * fix namespaces on tests * composer + tests: use standard test namespace naming * update travis * resolve conflict * phpstan lvl 2 * phpstan lvl 3 * phpstan lvl 4 * phpstan lvl 5 * phpstan lvl 6 * phpstan lvl 7 * level max * resolve conflict * [cs] clean empty docs * composer: bump to PHPUnit 6.4 * cleanup * composer + travis: add phpstan * phpstan lvl 1 * composer: update dev deps * phpstan fixes * update Contributing with new tools * docs: link fixes, PHP version update * composer: drop php-cs-fixer, cs already handled by ecs * ecs: add old set rules * [cs] apply rest of rules
65 lines
2.4 KiB
PHP
65 lines
2.4 KiB
PHP
<?php
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declare(strict_types=1);
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namespace Phpml\Tests\Classification\Ensemble;
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use Phpml\Classification\Ensemble\AdaBoost;
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use Phpml\ModelManager;
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use PHPUnit\Framework\TestCase;
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class AdaBoostTest extends TestCase
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{
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public function testPredictSingleSample()
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{
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// AND problem
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$samples = [[0.1, 0.3], [1, 0], [0, 1], [1, 1], [0.9, 0.8], [1.1, 1.1]];
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$targets = [0, 0, 0, 1, 1, 1];
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$classifier = new AdaBoost();
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$classifier->train($samples, $targets);
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$this->assertEquals(0, $classifier->predict([0.1, 0.2]));
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$this->assertEquals(0, $classifier->predict([0.1, 0.99]));
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$this->assertEquals(1, $classifier->predict([1.1, 0.8]));
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// OR problem
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$samples = [[0, 0], [0.1, 0.2], [0.2, 0.1], [1, 0], [0, 1], [1, 1]];
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$targets = [0, 0, 0, 1, 1, 1];
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$classifier = new AdaBoost();
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$classifier->train($samples, $targets);
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$this->assertEquals(0, $classifier->predict([0.1, 0.2]));
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$this->assertEquals(1, $classifier->predict([0.1, 0.99]));
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$this->assertEquals(1, $classifier->predict([1.1, 0.8]));
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// XOR problem
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$samples = [[0.1, 0.2], [1., 1.], [0.9, 0.8], [0., 1.], [1., 0.], [0.2, 0.8]];
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$targets = [0, 0, 0, 1, 1, 1];
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$classifier = new AdaBoost(5);
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$classifier->train($samples, $targets);
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$this->assertEquals(0, $classifier->predict([0.1, 0.1]));
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$this->assertEquals(1, $classifier->predict([0, 0.999]));
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$this->assertEquals(0, $classifier->predict([1.1, 0.8]));
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return $classifier;
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}
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public function testSaveAndRestore(): void
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{
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// Instantinate new Percetron trained for OR problem
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$samples = [[0, 0], [1, 0], [0, 1], [1, 1]];
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$targets = [0, 1, 1, 1];
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$classifier = new AdaBoost();
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$classifier->train($samples, $targets);
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$testSamples = [[0, 1], [1, 1], [0.2, 0.1]];
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$predicted = $classifier->predict($testSamples);
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$filename = 'adaboost-test-'.random_int(100, 999).'-'.uniqid();
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$filepath = tempnam(sys_get_temp_dir(), $filename);
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$modelManager = new ModelManager();
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$modelManager->saveToFile($classifier, $filepath);
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$restoredClassifier = $modelManager->restoreFromFile($filepath);
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$this->assertEquals($classifier, $restoredClassifier);
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$this->assertEquals($predicted, $restoredClassifier->predict($testSamples));
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}
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}
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