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<?php
use TeamTNT\TNTSearch\Classifier\TNTClassifier;
class TNTClassifierTest extends PHPUnit\Framework\TestCase
{
public function testPredictSpamHam()
{
$smsJSON = file_get_contents(__DIR__.'/../_files/sms-texts.json');
$sms = json_decode($smsJSON);
$training = 0.80;
$classifier = new TNTClassifier();
for ($i = 0; $i <= count($sms) * $training; $i++) {
$classifier->learn($sms[$i]->message, $sms[$i]->label);
}
$guessCount = 0;
$counter = 0;
for ($i = round(count($sms) * $training); $i < count($sms); $i++) {
$counter++;
$guess = $classifier->predict($sms[$i]->message);
if ($guess['label'] == $sms[$i]->label) {
$guessCount++;
}
}
$precision = number_format(($guessCount * 100 / $counter), 4);
$this->assertGreaterThanOrEqual(98, $precision);
}
public function testPredictClass()
{
$classifier = new TNTClassifier();
$classifier->learn("chinese beijing chinese", "c");
$classifier->learn("chinese chinese shangai", "c");
$classifier->learn("chinese macao", "c");
$classifier->learn("tokyo japan chinese", "j");
$guess = $classifier->predict("chinese chinese chinese tokyo japan");
$this->assertEquals("c", $guess['label']);
}
public function testPredictClass2()
{
$classifier = new TNTClassifier();
$classifier->learn("A great game", "Sports");
$classifier->learn("The election was over", "Not sports");
$classifier->learn("Very clean match", "Sports");
$classifier->learn("A clean but forgettable game", "Sports");
$guess = $classifier->predict("It was a close election");
$this->assertEquals("Not sports", $guess['label']);
}
}