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)
