NAME

       profnet_* - neural network implementations in Fortran

SYNOPSIS

       profnet_* [OPTION|filePar]

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 only as
       part of wrapping (dependent) packages and not as a standalone neural network program.

OPTIONS

       This list is not exhaustive.

       filePar
           file with input parameters (also gives fileIn, fileOut)

       1   "switch"

       2   number of input units

       3   number of hidden units

       4   number of output units

       5   number of samples

       6   bitacc (typically 100)

       7   file with input vectors

       8   file with junctions

       9   file with output of NN ("none" -> no file written)

       10  optional=dbg

       [inter]
           will bring up dialog

NOTES

       1st MUST be "switch"!

       tested only with 2 layers!

AUTHOR

       Burkhard Rost <rost@rostlab.org>

       Bug fixes and enhancements by Laszlo Kajan <lkajan@rostlab.org> and Guy Yachdav
       <gyachdav@rostlab.org>

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)