Phpml\SupportVectorMachine\SupportVectorMachine::predict PHP Method

    public function predict(array $samples)
    {
        $testSet = DataTransformer::testSet($samples);
        file_put_contents($testSetFileName = $this->varPath . uniqid(), $testSet);
        file_put_contents($modelFileName = $testSetFileName . '-model', $this->model);
        $outputFileName = $testSetFileName . '-output';
        $command = sprintf('%ssvm-predict%s %s %s %s', $this->binPath, $this->getOSExtension(), $testSetFileName, $modelFileName, $outputFileName);
        $output = '';
        exec(escapeshellcmd($command), $output);
        $predictions = file_get_contents($outputFileName);
        unlink($testSetFileName);
        unlink($modelFileName);
        unlink($outputFileName);
        if (in_array($this->type, [Type::C_SVC, Type::NU_SVC])) {
            $predictions = DataTransformer::predictions($predictions, $this->labels);
        } else {
            $predictions = explode(PHP_EOL, trim($predictions));
        }
        if (!is_array($samples[0])) {
            return $predictions[0];
        }
        return $predictions;
    }

 public function testPredictSampleFromMultipleClassWithRbfKernel()
 {
     $samples = [[1, 3], [1, 4], [1, 4], [3, 1], [4, 1], [4, 2], [-3, -1], [-4, -1], [-4, -2]];
     $labels = ['a', 'a', 'a', 'b', 'b', 'b', 'c', 'c', 'c'];
     $svm = new SupportVectorMachine(Type::C_SVC, Kernel::RBF, 100.0);
     $svm->train($samples, $labels);
     $predictions = $svm->predict([[1, 5], [4, 3], [-4, -3]]);
     $this->assertEquals('a', $predictions[0]);
     $this->assertEquals('b', $predictions[1]);
     $this->assertEquals('c', $predictions[2]);
 }