86 lines
3.0 KiB
PHP
86 lines
3.0 KiB
PHP
<?php
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declare (strict_types = 1);
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namespace tests\Phpml\Metric;
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use Phpml\Metric\ClassificationReport;
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class ClassificationReportTest extends \PHPUnit_Framework_TestCase
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{
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public function testClassificationReportGenerateWithStringLabels()
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{
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$labels = ['cat', 'ant', 'bird', 'bird', 'bird'];
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$predicted = ['cat', 'cat', 'bird', 'bird', 'ant'];
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$report = new ClassificationReport($labels, $predicted);
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$precision = ['cat' => 0.5, 'ant' => 0.0, 'bird' => 1.0];
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$recall = ['cat' => 1.0, 'ant' => 0.0, 'bird' => 0.67];
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$f1score = ['cat' => 0.67, 'ant' => 0.0, 'bird' => 0.80];
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$support = ['cat' => 1, 'ant' => 1, 'bird' => 3];
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$average = ['precision' => 0.75, 'recall' => 0.83, 'f1score' => 0.73];
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$this->assertEquals($precision, $report->getPrecision(), '', 0.01);
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$this->assertEquals($recall, $report->getRecall(), '', 0.01);
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$this->assertEquals($f1score, $report->getF1score(), '', 0.01);
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$this->assertEquals($support, $report->getSupport(), '', 0.01);
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$this->assertEquals($average, $report->getAverage(), '', 0.01);
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}
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public function testClassificationReportGenerateWithNumericLabels()
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{
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$labels = [0, 1, 2, 2, 2];
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$predicted = [0, 0, 2, 2, 1];
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$report = new ClassificationReport($labels, $predicted);
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$precision = [0 => 0.5, 1 => 0.0, 2 => 1.0];
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$recall = [0 => 1.0, 1 => 0.0, 2 => 0.67];
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$f1score = [0 => 0.67, 1 => 0.0, 2 => 0.80];
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$support = [0 => 1, 1 => 1, 2 => 3];
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$average = ['precision' => 0.75, 'recall' => 0.83, 'f1score' => 0.73];
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$this->assertEquals($precision, $report->getPrecision(), '', 0.01);
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$this->assertEquals($recall, $report->getRecall(), '', 0.01);
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$this->assertEquals($f1score, $report->getF1score(), '', 0.01);
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$this->assertEquals($support, $report->getSupport(), '', 0.01);
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$this->assertEquals($average, $report->getAverage(), '', 0.01);
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}
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public function testPreventDivideByZeroWhenTruePositiveAndFalsePositiveSumEqualsZero()
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{
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$labels = [1, 2];
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$predicted = [2, 2];
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$report = new ClassificationReport($labels, $predicted);
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$this->assertEquals([1 => 0.0, 2 => 0.5], $report->getPrecision(), '', 0.01);
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}
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public function testPreventDivideByZeroWhenTruePositiveAndFalseNegativeSumEqualsZero()
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{
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$labels = [2, 2, 1];
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$predicted = [2, 2, 3];
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$report = new ClassificationReport($labels, $predicted);
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$this->assertEquals([1 => 0.0, 2 => 1, 3 => 0], $report->getPrecision(), '', 0.01);
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}
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public function testPreventDividedByZeroWhenPredictedLabelsAllNotMatch()
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{
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$labels = [1,2,3,4,5];
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$predicted = [2,3,4,5,6];
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$report = new ClassificationReport($labels, $predicted);
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$this->assertEquals([
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'precision' => 0,
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'recall' => 0,
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'f1score' => 0
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], $report->getAverage(), '', 0.01);
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}
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}
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