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File: example/example.php

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  Classes of Cesar D. Rodas  >  Bayesian Spam Filter  >  example/example.php  >  Download  
File: example/example.php
Role: Example script
Content type: text/plain
Description: Classification example
Class: Bayesian Spam Filter
Detect spam in text using Bayesian techniques
Author: By
Last change: + Adding new algorithm ( Fisher-Robinson's Inverse Chi-square )
+ Decreasing knowledge database size.
+ Getting results.
+ Adding test.
Date: 7 years ago
Size: 3,526 bytes
 

Contents

Class file image Download
<?php
/*
***************************************************************************
* Copyright (C) 2007 by Cesar D. Rodas *
* cesar@sixdegrees.com.br *
* *
* Permission is hereby granted, free of charge, to any person obtaining *
* a copy of this software and associated documentation files (the *
* "Software"), to deal in the Software without restriction, including *
* without limitation the rights to use, copy, modify, merge, publish, *
* distribute, sublicense, and/or sell copies of the Software, and to *
* permit persons to whom the Software is furnished to do so, subject to *
* the following conditions: *
* *
* The above copyright notice and this permission notice shall be *
* included in all copies or substantial portions of the Software. *
* *
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, *
* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF *
* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.*
* IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR *
* OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, *
* ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR *
* OTHER DEALINGS IN THE SOFTWARE. *
***************************************************************************
*/
require("../spam.php");
require(
"config.php");
$db = mysql_connect(MYSQL_HOST,MYSQL_USER,MYSQL_PASS);
mysql_select_db(MYSQL_DB,$db);
/**
 *
 * Because the system do not manage a method where you
 * can save the data, you must define a function which recives
 * the wanted "n-grams" and return and array which is
 * "n-grams" and percent of accuracy (what its learn with example_trainer).
 * In this example those datas are loaded from mysql.
 *
 */
$spam = new spam("handler");
/**/
$texts = array("Phentermine", "Buy cheap xxx","Really nice post","Viagra","This a large text, it is not spam, but because the training set are small sentenses, it may be marked as spam. You can solve this problem with a largest sentences on the training set.");
echo
"<h1>Spam test</h1>";
foreach (
$texts as $text)
    echo
"<em><strong>$text</strong></em> has an accuraccy of <b>". $spam->isItSpam_v2($text,'spam')."%</b> spam<hr>";
echo
"<h1>Ham test</h1>";
foreach (
$texts as $text)
    echo
"<em><strong>$text</strong></em> has an accuraccy of <b>". $spam->isItSpam_v2($text,'1')."%</b> ham<hr>";;
/**
 * Callback function
 *
 * This is function is called by the classifier class, and it must
 * return all the n-grams.
 *
 * @param Array $ngrams N-grams.
 * @param String $type Type of set to compare
 */
function handler($ngrams,$type) {
    global
$db;
   
   
$info = array_keys($ngrams);
   
   
$sql = "select ngram,percent from knowledge_base where belongs = '$type' && ngram in ('".implode("','",$info)."')";
   
$r = mysql_query($sql,$db);
   
    while (
$row = mysql_fetch_array($r) ) {
       
$t[ $row['ngram'] ] = $row['percent'];
    }

    return
$t;
}
?>