Camspiers\StatisticalClassifier\Classifier\ComplementNaiveBayes::classify PHP Method

    public function classify($document)
    {
        $results = array();
        if ($this->documentNormalizer) {
            $document = $this->documentNormalizer->normalize($document);
        }
        $tokens = $this->tokenizer->tokenize($document);
        if ($this->tokenNormalizer) {
            $tokens = $this->tokenNormalizer->normalize($tokens);
        }
        $tokens = array_count_values($tokens);
        $weights = $this->preparedModel()->getModel();
        foreach (array_keys($weights) as $category) {
            $results[$category] = 0;
            foreach ($tokens as $token => $count) {
                if (array_key_exists($token, $weights[$category])) {
                    $results[$category] += $count * $weights[$category][$token];
                }
            }
        }
        asort($results, SORT_NUMERIC);
        $category = key($results);
        $value = array_shift($results);
        if ($value === array_shift($results)) {
            return false;
        } else {
            return $category;
        }
    }

<?php

require_once __DIR__ . '/../vendor/autoload.php';
// Using a plain data array source for simplicity
use Camspiers\StatisticalClassifier\DataSource\DataArray;
use Camspiers\StatisticalClassifier\Classifier\ComplementNaiveBayes;
$source = new DataArray(array(array('category' => 'spam', 'document' => 'Some spam document'), array('category' => 'spam', 'document' => 'Another spam document'), array('category' => 'ham', 'document' => 'Some ham document'), array('category' => 'ham', 'document' => 'Another ham document')));
$source->addDocument('spam', 'Another spam document');
$source->addDocument('ham', 'Another ham document');
$c = new ComplementNaiveBayes($source);
echo $c->classify("Some ham document"), PHP_EOL;