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 __construct( DataSourceInterface $dataSource, ModelInterface $model = null, Document\NormalizerInterface $documentNormalizer = null, TokenizerInterface $tokenizer = null, Token\NormalizerInterface $tokenNormalizer = null )
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<?php
/**
* This file is part of the Statistical Classifier package.
*
* (c) Cam Spiers <camspiers@gmail.com>
*
* For the full copyright and license information, please view the LICENSE
* file that was distributed with this source code.
*/
namespace Camspiers\StatisticalClassifier\Classifier;
use Camspiers\StatisticalClassifier\DataSource\DataSourceInterface;
use Camspiers\StatisticalClassifier\Model\Model;
use Camspiers\StatisticalClassifier\Model\ModelInterface;
use Camspiers\StatisticalClassifier\Normalizer\Document;
use Camspiers\StatisticalClassifier\Normalizer\Token;
use Camspiers\StatisticalClassifier\Tokenizer\TokenizerInterface;
use Camspiers\StatisticalClassifier\Tokenizer\Word;
use Camspiers\StatisticalClassifier\Transform;
/**
* An implementation of a Naive Bayes classifier.
*
* This classifier is based off *Tackling the Poor Assumptions of Naive Bayes Text Classifiers* by Jason Rennie
* @author Cam Spiers <camspiers@gmail.com>
* @package Statistical Classifier
*/
class ComplementNaiveBayes extends Classifier
{
/**
* Tokenizer (the way of breaking up documents)
* @var TokenizerInterface
*/
protected $tokenizer;
/**
* Takes document and makes it consistent
* @var Document\NormalizerInterface
*/
protected $documentNormalizer;
/**
* Takes tokenized data and makes it consistent or stem it
* @var Token\NormalizerInterface
*/
protected $tokenNormalizer;
/**
* Create the Naive Bayes Classifier
* @param DataSourceInterface $dataSource
* @param ModelInterface $model An model to store data in
* @param Document\NormalizerInterface $documentNormalizer The normalizer to make document consistent
* @param TokenizerInterface $tokenizer The tokenizer to break up the documents
* @param Token\NormalizerInterface $tokenNormalizer The normaizer to make tokens consistent
*/
public function __construct(
DataSourceInterface $dataSource,
ModelInterface $model = null,
Document\NormalizerInterface $documentNormalizer = null,
TokenizerInterface $tokenizer = null,
Token\NormalizerInterface $tokenNormalizer = null
) {
$this->dataSource = $dataSource;
$this->model = $model ?: new Model();
$this->documentNormalizer = $documentNormalizer ?: new Document\Lowercase();
$this->tokenizer = $tokenizer ?: new Word();
$this->tokenNormalizer = $tokenNormalizer;
}
/**
* @inheritdoc
*/
public function prepareModel()
{
$data = $this->applyTransform(
new Transform\TokenPreparation(
$this->tokenizer,
$this->documentNormalizer,
$this->tokenNormalizer
),
$this->dataSource->getData()
);
$tokenCountByDocument = $this->applyTransform(
new Transform\TokenCountByDocument(),
$data
);
$documentCount = $this->applyTransform(
new Transform\DocumentCount(),
$data
);
unset($data);
$tokenAppearanceCount = $this->applyTransform(
new Transform\TokenAppearanceCount(),
$tokenCountByDocument
);
$tokensByCateory = $this->applyTransform(
new Transform\TokensByCategory(),
$tokenCountByDocument
);
$tfidf = $this->applyTransform(
new Transform\TFIDF(),
$tokenCountByDocument,
$documentCount,
$tokenAppearanceCount
);
unset($tokenCountByDocument);
unset($tokenAppearanceCount);
$documentLength = $this->applyTransform(
new Transform\DocumentLength(),
$tfidf
);
unset($tfidf);
$documentTokenCounts = $this->applyTransform(
new Transform\DocumentTokenCounts(),
$documentLength
);
$complement = $this->applyTransform(
new Transform\Complement(),
$documentLength,
$tokensByCateory,
$documentCount,
$documentTokenCounts
);
unset(
$documentLength,
$tokensByCateory,
$documentCount,
$documentTokenCounts
);
$this->model->setModel(
$this->applyTransform(
new Transform\Weight(),
$complement
)
);
$this->model->setPrepared(true);
}
/**
* @inheritdoc
*/
public function classify($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;
}
}
}