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A Bayesian Classification Library in PHP
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README.md

Wotsit - A Bayesian Classification Library for PHP

Installation

Install PHPUnit

sudo pear channel-discover pear.phpunit.de
sudo pear install phpunit/PHPUnit

Install Phing

sudo pear channel-discover pear.phing.info
sudo pear install phing/phing

Building

Wotsit is designed to be packaged as a phar file. To create the package run: phing build-all This will build run all tests, create documentation (in the /docs folder) and creates the Wotsit.phar file

Usage

Basic Usage

With a pre-trained classifier: require 'Wotsit.phar'; //initialise storage object with previously learned data $storage = new wotsit_storage_Dbm('data.db');

$extractor = new wotsit_feature_WordExtractor();
$classfier = new wotsit_classifier_NaiveBayesian($extractor, $storage);

//classify the passed in text
$category = $classfier->classify($someText);

Training: require 'Wotsit.phar'; $storage = new wotsit_storage_Dbm('new.db');

$extractor = new wotsit_feature_WordExtractor(); //NB: You can also pass in a stemmer if you desire
$classfier = new wotsit_classifier_NaiveBayesian($extractor, $storage);

$goodData = array(); //should be examples of documents which are in the category 'good'
$badData = array(); //should be examples of documents which are in the category 'bad'

//Adding examples of 'good' data
foreach ($goodData as $goodDatum) {
    $classfier->train($goodDatum, 'good');
}

//adding examples of 'bad' data
foreach ($badData as $badDatum) {
    $classfier->train($badDatum, 'bad');
}

For more informtaion see the API documentation which can be build by running: phing api-docs

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