PHP Classes

PHP Neural Network Library: Implements a multilayer perceptron neural network

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Version License PHP version Categories
php-nn 1.0.0The PHP License5PHP 5, Artificial intelligence
Description 

Author

This package implements a multilayer perceptron neural network.

It provides classes that implement networks, nodes and links that can be assembled to create a neural network.

The network can be activated using a matrix of weights that defines how the outputs of each node are computed from the input values.

It can also train the network with the same input data processing the epoch data several multiple times.

A very rudimentary MLP network implementation in PHP. Can be used for reference but no longer maintained

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Name: Rizza <contact>
Classes: 2 packages by
Country: United Kingdom
Age: ???
All time rank: 3763162 in United Kingdom
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Example

<?php
require_once(__DIR__."/class/node.php");
require_once(
__DIR__."/class/network.php");
require_once(
__DIR__."/class/link.php");
require_once(
__DIR__."/func/activate.php");
ini_set('xdebug.var_display_max_depth', 5);
ini_set('xdebug.var_display_max_children', 256);
ini_set('xdebug.var_display_max_data', 1024);
ini_set('xdebug.max_nesting_level', 200);
srand(time());
$x=new \nn\network([2,2,2,1]);
echo
"<pre>";
//var_dump($x);
echo "</pre>";
error_reporting(E_ALL); ini_set('display_errors', 1);
//print_r($x->activate([1,2,2]));
foreach(
    [
        [[
1,1],[0]],
        [[
1,0],[1]],
        [[
0,1],[1]],
        [[
0,0],[0]]
    ]
    as
$y
   
){
       
      
print_r($y[0]);
      
print_r($x->activate($y[0]));
        echo(
"<br/>");
    }
set_time_limit(9001);
foreach(
range(1,100000) as $k){
   
$mse=0;
    foreach(
        [
            [[
1,1],[0]],
            [[
1,0],[1]],
            [[
0,1],[1]],
            [[
0,0],[0]]
        ]
        as
$y
       
){
           
$mse+=$x->epoch($y[0],$y[1]);
           
        }
       
//echo("<br/>");
        //echo $mse/2;
}

foreach(
    [
        [[
1,1],[1]],
        [[
1,0],[0]],
        [[
0,1],[0]],
        [[
0,0],[0]]
    ]
    as
$y
   
){
      
print_r($y[0]);
      
print_r($x->activate($y[0]));
        echo(
"<br/>");
    }


Details

php-nn

This is my first attempt at implamenting a multilayer perceptron neural network in php. Currently the network uses a standard backpropogation algorithm to train. This project will be updated with newer training methods shortly.


  Files folder image Files  
File Role Description
Files folder imageOO (2 files, 2 directories)
Files folder imageProcedural (2 files, 1 directory)
Accessible without login Plain text file .buildpath Data Auxiliary data
Accessible without login Plain text file .project Data Auxiliary data
Accessible without login Plain text file LICENSE Lic. License text
Accessible without login Plain text file README.md Doc. Documentation

  Files folder image Files  /  OO  
File Role Description
Files folder imageclass (3 files)
Files folder imagefunc (1 file)
  Accessible without login Plain text file core.php Example Example script
  Accessible without login Plain text file README.md Doc. Documentation

  Files folder image Files  /  OO  /  class  
File Role Description
  Plain text file link.php Class Class source
  Plain text file network.php Class Class source
  Plain text file node.php Class Class source

  Files folder image Files  /  OO  /  func  
File Role Description
  Accessible without login Plain text file activate.php Aux. Auxiliary script

  Files folder image Files  /  Procedural  
File Role Description
Files folder imageclasses (1 file)
  Accessible without login Plain text file index.php Example Example script
  Accessible without login Plain text file README.md Doc. Documentation

  Files folder image Files  /  Procedural  /  classes  
File Role Description
  Plain text file network.php Class Class source

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