146 lines
3.3 KiB
PHP
146 lines
3.3 KiB
PHP
<?php
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namespace Rubix\ML\Tests\Classifiers;
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use Rubix\ML\Learner;
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use Rubix\ML\DataType;
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use Rubix\ML\Estimator;
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use Rubix\ML\Persistable;
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use Rubix\ML\EstimatorType;
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use Rubix\ML\Other\Strategies\Prior;
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use Rubix\ML\Datasets\Generators\Blob;
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use Rubix\ML\Classifiers\DummyClassifier;
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use Rubix\ML\Datasets\Generators\Agglomerate;
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use Rubix\ML\CrossValidation\Metrics\Accuracy;
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use PHPUnit\Framework\TestCase;
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/**
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* @group Classifiers
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* @covers \Rubix\ML\Classifiers\DummyClassifier
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*/
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class DummyClassifierTest extends TestCase
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{
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/**
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* The number of samples in the training set.
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*
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* @var int
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*/
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protected const TRAIN_SIZE = 100;
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/**
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* The number of samples in the validation set.
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*
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* @var int
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*/
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protected const TEST_SIZE = 10;
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/**
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* The minimum validation score required to pass the test.
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*
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* @var float
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*/
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protected const MIN_SCORE = 0.0;
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/**
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* Constant used to see the random number generator.
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*
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* @var int
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*/
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protected const RANDOM_SEED = 0;
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/**
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* @var \Rubix\ML\Datasets\Generators\Agglomerate
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*/
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protected $generator;
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/**
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* @var \Rubix\ML\Classifiers\DummyClassifier
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*/
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protected $estimator;
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/**
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* @var \Rubix\ML\CrossValidation\Metrics\Accuracy
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*/
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protected $metric;
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/**
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* @before
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*/
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protected function setUp() : void
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{
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$this->generator = new Agglomerate([
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'red' => new Blob([255, 32, 0], 30.0),
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'green' => new Blob([0, 128, 0], 10.0),
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'blue' => new Blob([0, 32, 255], 20.0),
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], [2, 3, 4]);
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$this->estimator = new DummyClassifier(new Prior());
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$this->metric = new Accuracy();
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srand(self::RANDOM_SEED);
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}
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/**
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* @test
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*/
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public function build() : void
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{
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$this->assertInstanceOf(DummyClassifier::class, $this->estimator);
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$this->assertInstanceOf(Learner::class, $this->estimator);
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$this->assertInstanceOf(Estimator::class, $this->estimator);
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$this->assertInstanceOf(Persistable::class, $this->estimator);
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}
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/**
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* @test
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*/
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public function type() : void
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{
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$this->assertEquals(EstimatorType::classifier(), $this->estimator->type());
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}
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/**
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* @test
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*/
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public function compatibility() : void
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{
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$this->assertEquals(DataType::all(), $this->estimator->compatibility());
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}
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/**
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* @test
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*/
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public function params() : void
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{
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$expected = [
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'strategy' => new Prior(),
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];
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$this->assertEquals($expected, $this->estimator->params());
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}
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/**
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* @test
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*/
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public function trainPredict() : void
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{
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$training = $this->generator->generate(self::TRAIN_SIZE);
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$testing = $this->generator->generate(self::TEST_SIZE);
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$this->estimator->train($training);
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$this->assertTrue($this->estimator->trained());
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$predictions = $this->estimator->predict($testing);
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$score = $this->metric->score($predictions, $testing->labels());
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$this->assertGreaterThanOrEqual(self::MIN_SCORE, $score);
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}
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protected function assertPreConditions() : void
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{
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$this->assertFalse($this->estimator->trained());
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}
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}
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