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3523017 Apr 5, 2017
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<?php declare(strict_types=1);
namespace PhpmlExamples;
include 'vendor/autoload.php';
use Phpml\Dataset\CsvDataset;
use Phpml\Dataset\ArrayDataset;
use Phpml\FeatureExtraction\TokenCountVectorizer;
use Phpml\Tokenization\WordTokenizer;
use Phpml\CrossValidation\StratifiedRandomSplit;
use Phpml\FeatureExtraction\TfIdfTransformer;
use Phpml\Metric\Accuracy;
use Phpml\Classification\SVC;
use Phpml\SupportVectorMachine\Kernel;
$dataset = new CsvDataset('data/languages.csv', 1);
$vectorizer = new TokenCountVectorizer(new WordTokenizer());
$tfIdfTransformer = new TfIdfTransformer();
$samples = [];
foreach ($dataset->getSamples() as $sample) {
$samples[] = $sample[0];
}
$vectorizer->fit($samples);
$vectorizer->transform($samples);
$tfIdfTransformer->fit($samples);
$tfIdfTransformer->transform($samples);
$dataset = new ArrayDataset($samples, $dataset->getTargets());
$randomSplit = new StratifiedRandomSplit($dataset, 0.1);
$classifier = new SVC(Kernel::RBF, 10000);
$classifier->train($randomSplit->getTrainSamples(), $randomSplit->getTrainLabels());
$predictedLabels = $classifier->predict($randomSplit->getTestSamples());
echo 'Accuracy: '.Accuracy::score($randomSplit->getTestLabels(), $predictedLabels);