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=head1 NAME
profnet_* - neural network implementations in Fortran
=head1 SYNOPSIS
profnet_* [OPTION|filePar]
=head1 DESCRIPTION
profnet_* binaries are neural network implementations in Fortran. Due to the original design of the code, a specific binary is compiled for each particular network architecture, changing certain constants in the source code. Therefore, there is a binary for every network architecture used. Note: certain array structures are intentionally indexed out of bounds in some of the binaries.
Note:
This binary should only be used to run with pre-made training data, do not try to use it to train your network as it will produce undesired results. It was made to be used I<only> as part of wrapping (dependent) packages and not as a standalone neural network program.
=head1 OPTIONS
This list is not exhaustive.
=over
=item filePar
file with input parameters (also gives fileIn, fileOut)
=item 1
"switch"
=item 2
number of input units
=item 3
number of hidden units
=item 4
number of output units
=item 5
number of samples
=item 6
bitacc (typically 100)
=item 7
file with input vectors
=item 8
file with junctions
=item 9
file with output of NN ("none" -> no file written)
=item 10
optional=dbg
=item [inter]
will bring up dialog
=back
=head1 NOTES
1st MUST be "switch"!
tested only with 2 layers!
=head1 AUTHOR
Burkhard Rost <rost@rostlab.org>
Bug fixes and enhancements by Laszlo Kajan <lkajan@rostlab.org> and Guy Yachdav <gyachdav@rostlab.org>
=head1 COPYRIGHT AND LICENSE
Copyright 1998-2011 by Burkhard Rost <rost@rostlab.org> EMBL, CUBIC (Columbia University, NY, USA) and LION Biosciences (Heidelberg, DE)
Copyright 2009-2011 by Laszlo Kajan <lkajan@rostlab.org> Technical University Munich (Munich, DE)
Copyright 2009-2011 by Guy Yachdav <gyachdav@rostlab.org> CUBIC (Columbia University, NY, USA) and Technical University Munich (Munich, DE)
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