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Contributor - Neural Network module


Provides a Neural Network Toolbox for Scilab.


Several libraries exist. From these libraries, two main libraries can be highlighted:

Work done

A first version of an interface to FANN has been developped on version fann-2.1.0beta. Every fann functions are interfaced to scilab. Here is an example of a scilab-fann script:

filename = 'abelone.train'; 
max_epochs      = 1000; 
desired_error   = 1e-5; 
cascade_neurons = 100; 
UseStandardLearning = %T; 
UseCascadeLearning  = %F;

ann_train_data  = read_train_from_file(filename);

num_input = setup_train_data(ann_train_data,'num_input_train_data');
num_output = setup_train_data(ann_train_data,'num_output_train_data');
td_length = setup_train_data(ann_train_data,'length_train_data');

printf('Filename = %s\n',filename);
printf('Number of inputs = %d\n',num_input);
printf('Number of outputs = %d\n',num_output);
printf('Length of the data set = %d\n',td_length);

ann = createfann('sparse',[num_input 2 num_output], 0.8);

ann = setup_train_data(ann_train_data,'set_input_scaling_params',ann,-1,1);
ann = setup_train_data(ann_train_data,'set_output_scaling_params',ann,-1,1);

ann = setparametersfann(ann,'activation_function_hidden','FANN_SIGMOID_SYMMETRIC');
ann = setparametersfann(ann,'activation_function_output','FANN_LINEAR');

ann = setparametersfann(ann,'training_algorithm','FANN_TRAIN_RPROP');
ann = setparametersfann(ann,'train_error_function','FANN_ERRORFUNC_LINEAR');
ann = setparametersfann(ann,'train_stop_function','FANN_STOPFUNC_MSE');

ann = reset_MSE(ann); t_start = getdate();
ann = train_on_data(ann, ann_train_data, max_epochs, desired_error);
printf('End of the training phase after %d sec.\n',etime(getdate(),t_start));

Up to now, the fann-toolbox is available on request (send a mail to ycollet et freesurf dot fr) because some parts are lacking:

All the sources are hosted at http://code.google.com/p/scifann/.

2022-09-08 09:26