https://github.com/camspiers/statistical-classifier

A PHP implementation of a Naive Bayes statistical classifier, including a structure for building other classifiers, multiple data sources and multiple caching backends.
https://github.com/camspiers/statistical-classifier

Last synced: about 2 months ago
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A PHP implementation of a Naive Bayes statistical classifier, including a structure for building other classifiers, multiple data sources and multiple caching backends.

• Host: GitHub
• URL: https://github.com/camspiers/statistical-classifier
• Owner: camspiers
• License: mit
• Created: 2012-09-29T22:18:06.000Z (almost 12 years ago)
• Default Branch: master
• Last Pushed: 2016-09-26T20:55:35.000Z (almost 8 years ago)
• Last Synced: 2024-07-13T17:43:24.125Z (2 months ago)
• Language: PHP
• Homepage: http://camspiers.github.io/statistical-classifier/
• Size: 29.4 MB
• Stars: 175
• Watchers: 22
• Forks: 26
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# PHP Classifier

[![Build Status](https://travis-ci.org/camspiers/statistical-classifier.png?branch=master)](https://travis-ci.org/camspiers/statistical-classifier)

[![Latest Stable Version](https://poser.pugx.org/camspiers/statistical-classifier/v/stable.png)](https://packagist.org/packages/camspiers/statistical-classifier)

PHP Classifier uses [semantic versioning](http://semver.org/), it is currently at major version 0, so the public API should not be considered stable.

# What is it?

PHP Classifier is a text classification library with a focus on reuse, customizability and performance.

Classifiers can be used for many purposes, but are particularly useful in detecting spam.

## Features

* Complement Naive Bayes Classifier

* SVM (libsvm) Classifier

* Highly customizable (easily modify or build your own classifier)

* Command-line interface via separate library (phar archive)

* Multiple **data import types** to get your data into the classifier (Directory of files, Database queries, Json, Serialized arrays)

* Multiple types of **model caching**

* Compatible with HipHop VM

# Installation

```bash

$ composer require camspiers/statistical-classifier

```

## SVM Support

For SVM Support both libsvm and php-svm are required. For installation intructions refer to [php-svm](https://github.com/ianbarber/php-svm).

# Usage

## Non-cached Naive Bayes

```php

use Camspiers\StatisticalClassifier\Classifier\ComplementNaiveBayes;

use Camspiers\StatisticalClassifier\DataSource\DataArray;

$source = new DataArray();

$source->addDocument('spam', 'Some spam document');

$source->addDocument('spam', 'Another spam document');

$source->addDocument('ham', 'Some ham document');

$source->addDocument('ham', 'Another ham document');

$classifier = new ComplementNaiveBayes($source);

$classifier->is('ham', 'Some ham document'); // bool(true)

$classifier->classify('Some ham document'); // string "ham"

```

## Non-cached SVM

```php

use Camspiers\StatisticalClassifier\Classifier\SVM;

use Camspiers\StatisticalClassifier\DataSource\DataArray;

$source = new DataArray()

$source->addDocument('spam', 'Some spam document');

$source->addDocument('spam', 'Another spam document');

$source->addDocument('ham', 'Some ham document');

$source->addDocument('ham', 'Another ham document');

$classifier = new SVM($source);

$classifier->is('ham', 'Some ham document'); // bool(true)

$classifier->classify('Some ham document'); // string "ham"

```

# Caching models

Caching models requires [maximebf/CacheCache](https://github.com/maximebf/CacheCache) which can be installed via packagist. Additional caching systems can be easily integrated.

## Cached Naive Bayes

```php

use Camspiers\StatisticalClassifier\Classifier\ComplementNaiveBayes;

use Camspiers\StatisticalClassifier\Model\CachedModel;

use Camspiers\StatisticalClassifier\DataSource\DataArray;

$source = new DataArray();

$source->addDocument('spam', 'Some spam document');

$source->addDocument('spam', 'Another spam document');

$source->addDocument('ham', 'Some ham document');

$source->addDocument('ham', 'Another ham document');

$model = new CachedModel(

	'mycachename',

	new CacheCache\Cache(

		new CacheCache\Backends\File(

			array(

				'dir' => __DIR__

			)

		)

	)

);

$classifier = new ComplementNaiveBayes($source, $model);

$classifier->is('ham', 'Some ham document'); // bool(true)

$classifier->classify('Some ham document'); // string "ham"

```

## Cached SVM

```php

use Camspiers\StatisticalClassifier\Classifier\SVM;

use Camspiers\StatisticalClassifier\Model\SVMCachedModel;

use Camspiers\StatisticalClassifier\DataSource\DataArray;

$source = new DataArray();

$source->addDocument('spam', 'Some spam document');

$source->addDocument('spam', 'Another spam document');

$source->addDocument('ham', 'Some ham document');

$source->addDocument('ham', 'Another ham document');

$model = new Model\SVMCachedModel(

	__DIR__ . '/model.svm',

	new CacheCache\Cache(

		new CacheCache\Backends\File(

			array(

				'dir' => __DIR__

			)

		)

	)

);

$classifier = new SVM($source, $model);

$classifier->is('ham', 'Some ham document'); // bool(true)

$classifier->classify('Some ham document'); // string "ham"

```

# Unit testing

    statistical-classifier/ $ composer install --dev

    statistical-classifier/ $ phpunit