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Back Propagation Scale: Implement neural networks using back propagation

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Name: freedelta <contact>
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Country: France France
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This class can be used to implement neural networks using back propagation.

It can setup a neural network work with a given number of layers.

The class takes a data set and a test output data set and runs the neural network using back propagation to to adjust weights based on network errors.

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Name: Back Propagation Scale
Base name: back-propagation
Description: Implement neural networks using back propagation
Version: 1.0.0
PHP version: 3.0
License: Free For Educational Use
All time users: 956 users
All time rank: 3489
Week users: 2 users
Week rank: 975 Up
 
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  Innovation Award  
PHP Programming Innovation award nominee
March 2010
Number 2


Prize: One book of choice by Apress
Back propagation is a well known algorithm to implement neural networks.

It works by self-adjusting the weights of each neuron by propagating from the output to the input weights by evaluating the difference between the expected results and the current results during the training phase.

This class provides a PHP implementation of the back propagation algorithm.

Manuel Lemos

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Accessible without login Plain text file class.BackPropagationScale.php Class BackPropagation With Scale
Accessible without login Plain text file results Output Output data backpropagation

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