Hi, I have uploaded the new AI::FANN module to CPAN:
http://search.cpan.org/~salva/AI-FANN/ It is a wrapper for the Fast Artificial Neural Network library (http://fann.sf.net): Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. PHP, C++, .NET, Python, Delphi, Octave, Ruby, Pure Data and Mathematica bindings are available. A reference manual accompanies the library with examples and recommendations on how to use the library. A graphical user interface is also available for the library. This is an early release that may contain critical bugs, though most things seem to be working properly. The documentation focus on the differences with the C library, and both versions should be consulted in order to use the module. Training an ANN to emulate a XOR gate with AI::FANN looks like that: use AI::FANN qw(:all); # create an ANN with 2 inputs, a hidden layer with 3 neurons # and an output layer with 1 neuron: my $ann = AI::FANN->new_standard(2, 3, 1); $ann->hidden_activation_function(FANN_SIGMOID_SYMMETRIC); $ann->output_activation_function(FANN_SIGMOID_SYMMETRIC); # create the training data for a XOR operator: my $xor_train = AI::FANN::TrainData->new( [-1, -1], [-1], [-1, 1], [1], [1, -1], [1], [1, 1], [-1] ); $ann->train_on_data($xor_train, 500000, 1000, 0.001); $ann->save("xor.ann"); And using the trained ANN: use AI::FANN; my $ann = AI::FANN->new_from_file("xor.ann"); for my $a (-1, 1) { for my $b (-1, 1) { my $out = $ann->run([$a, $b]); printf "xor(%f, %f) = %f\n", $a, $b, $out->[0]; } } Comments and feedback are very welcome! Cheers, - Salva.
