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ANN - Artificial Neural Network for PHP
This project realizes a neural network topology called multilayer perceptron for PHP environments. The source code is based on a work by Eddy Young in 2002. Several improvements and changes on this implementation are done by Thomas Wien (thwien.de - Ratingen - Germany) since 2007. You will find the PHP source in the section Download. Please, consider the Copyright. To get a short idea what is the benefit of neural networks have a look at page Neural Networks.
Overview
Features
- Output type detection (linear or binary)
- Logging (weights and network errors)
- Client-Server model for distributed applications
- Graphical network topology as PNG image
- Displaying network details
- String association
- Classification
- Phar support (as of PHP 5.3.0)
Versions and Change-Log
Version 2.x.x by Thomas Wien (Development)
- Image matrix support
Version 2.3.0 by Thomas Wien (2012-12-13) Download * Using traits for performance reasons * Checking php version for compatibility with ANN library * PHP 5.4.x or above
Version 2.2.3 by Thomas Wien (2012-12-12) Download
- Bugfix: Division by zero if training time below one second
- Adding php version and sapi interface to network information
- Test running on PHP 5.4
Version 2.2.2 by Thomas Wien (2011-07-04)
- Redesign of network details
- Considering cpu limits for calculation of network execution time
Version 2.2.1 by Thomas Wien (2011-06-15)
- Bug fix: Wrong output type detection in binary networks
- Using Interface called \ANN\InterfaceLoadable to make easier decision of loadable objects.
Version 2.2.0 by Thomas Wien (2011-06-01)
- Introduction of namespaces as of PHP 5.3
- Dynamic learning rate
- \ANN\Network::setLearningRate() is protected now
- Bug fix: Wrong output type detection in some circumstances
Version 2.1.7 by Thomas Wien (2011-06-15) Download
- Bug fix: Wrong output type detection in binary networks
Version 2.1.6 by Thomas Wien (2011-06-01)
- Bug fix: Wrong output type detection in some circumstances
Version 2.1.5 by Thomas Wien (2011-05-24)
- Dividing method ANN_Math::random() in ANN_Math::randomDelta() and ANN_Math::randomWeight()
- Better implementation of printing network details including __invoke() und __toString() converting
Version 2.1.4 by Thomas Wien (2011-05-23)
- Better calculation of remaining time of running the network
- Fixing bug: generating random delta not correct
- Adding momentum value
- Simplified ANN_Neuron::adjustWeights()
- Remove possible wrong calculation in ANN_Neuron::adjustWeights() on linear networks
- Simplify ANN_Layer::calculateHiddenDeltas()
Version 2.1.3 by Thomas Wien (2010-01-06)
- Date input support class
Version 2.1.2 by Thomas Wien (2009-12-26)
- Classification support
- Phar support (as of PHP 5.3.0)
Version 2.1.1 by Thomas Wien (2009-12-23)
- String association support
Version 2.1.0 by Thomas Wien (2009-12-22)
- Checking parameter counts on ANN_Values::input() and ANN_Values::output()
- Removing protected method ANN_Neuron::getInputs()
- Fixing bug: Error tolerance calculation in ANN_Network::isTrainingComplete()
- Switching to Git version control
- Moving all experimental code into branch
- Removing all experimental code from master branch (due to performance and future development)
Version 2.0.7 by Thomas Wien (2009-01-01) Download
- Removing protected method ANN_Neuron::setOutput()
- Removing protected unused method ANN_Layer::getInputs()
- Removing protected unused property ANN_Layer::$arrInputs
- More detailed exceptions to ANN_Filesystem::saveToFile()
- Different distribution of activation calls across the layers
- Different adjustments in ANN_Neuron::adjustWeights() depending on output type
- Removing static local variables from ANN_Network::getNextIndexInputsToTrain()
- Increasing math precision
- Using class constants for output types (increasing performance)
- Fixing bug: ANN_Neuron::getOutput() is float and not array
Version 2.0.6 by Thomas Wien (2008-12-18)
- Printing network details of output differences to their desired values
- Complete rewritten code standard of variables
- New class ANN_Values for defining input and output values
- Code examples to phpdoc
- Internal math precision defaults to 5
Version 2.0.5 by Thomas Wien (2008-12-16)
- Adjustable output error tolerance between 0 and 10 per cent
- Internal rounding of floats for performance issues
- Loading class for all ANN classes (SPL autoload)
- Renaming filename of ANN_Maths class
- Improving code standard
- Fixing bug: Comparison in ANN_InputValue and ANN_OutputValue
Version 2.0.4 by Thomas Wien (2008-01-27)
- Weight decay
- QuickProp algorithm (experimental)
- RProp algorithm (experimental)
- Linear saturated activation function (experimental)
- Individual learning rate algorithm (experimental)
- Reducing of overfitting (no training if input pattern produces desired output)
- Increasing performance on activation
- Increasing performance on testing all patterns to their desired outputs
- Increasing performance on calculating hidden deltas
- Increasing performance by defining layer relation by construction
- More details to printNetwork()
- Fixing bug: learning rate is not part of saved delta value
Version 2.0.3 by Thomas Wien (2008-01-17)
- Support for dynamic learning rate
- Automatic epoch determination
- Automatic output type detection
- Shuffling input patterns each epoch instead of randomized pattern access
- Logging of network errors
- Logging on each epoch instead of each training step
- Avoiding distributed internal calls of setMomentum() and setLearningRate()
- Extending display of network details
- Fixing bug: runtime error on call of setMomentum()
Version 2.0.2 by Thomas Wien (2008-01-14)
- Client-Server model for distributed applications
- Calculating total network error for csv logging
Version 2.0.1 by Thomas Wien (2008-01-06)
- Separation of classes to several files
- Version control by Subversion
- Performance issues
- Graphical output of neural network topology
- Logging of weights to csv file
Version 2.0.0 by Thomas Wien (2007-12-17)
- PHP 5.x support
- PHPDoc documentation
- Momentum support
- Avoiding network overfitting
- Linear / binary output
- ANN_InputValue + ANN_OutputValue classes
- Exceptions
- Threshold function
- Hyperbolic tangent transfer function
- Several performance issues
- Avoiding array_keys() & srand() due to performance
- Changes in saving and loading network
- Printing network details to browser
- Fixing bug: initializing inputs to all hidden layers
- Fixing bug: training for first hidden layer was skipped
Version 1.0 by Eddy Young (2002)
- Initial version
Todo
- More Examples
- Performance check depending on host system
- Wiki: More details to installation and use
- PHPDoc: More details to documentation
- Improving license agreement of source code
- Adding error codes to exceptions
- Exception if network error does not reach minimum