New Features of SNNS 4.3
Version 4.3 of SNNS features the following improvements and extensions
over the earlier version 4.2:
- included patches avaiable from the SNNS-development project .
- License changed to LGPL v2.
- Fixed some bugs in the installation configuration files.
New Features of SNNS 4.2
Version 4.2 of SNNS features the following improvements and extensions
over the earlier version 4.1:
- greatly improved installation procedure
- pattern remapping functions introduced to SNNS
- class information in patterns introduced to SNNS
- change to all batch algorithms: The learning rate is now divided
by the number of patterns in the set. This allows for direct
comparisons of learning rates and training of large pattern files
with BP-Batch since it doesn't require ridiculous learning rates like
- Changes to Cascade-Correlation:
- Several modifications can be used to achieve a net with a
smaller depth or smaller Fan-In.
- New activation functions ACT_GAUSS and ACT_SIN
- The backpropagation algorithm of Cascade-Correlation is now
present in an offline and a batch version.
- The activations of the units could be cached. The result is
a faster learning for nets with many units. On the other hand,
the needed memory space will rise for large training patterns.
- Changes in the 2D-display, the hidden units are displayed
in layers, the candidate units are placed on the top of the net.
- validation now possible
- automatic deletion of candidate units at the end of training.
- new meta learning algorithm TACOMA.
- new learning algorithm BackpropChunk. It allows chunkwise
updating of the weights as well as selective training of units on the
basis of pattern class names.
- new learning algorithm RPROP with weight decay.
- algorithm ``Recurrent Cascade Correlation'' deleted from
- the options of adding noise to the weights with the JogWeights
function improved im multiple ways.
- improved plotting in the graph panel as well as printing option
- when standard colormap is full, SNNS will now start with a privat map
instead of aborting.
- analyze tool now features a confusion matrix.
- pruning panel now more ``SNNS-like''. You do not need to close
the panel anymore before pruning a network.
- Changes in batchman
- batchman can now handle DLVQ training
- new batchman command ``setActFunc'' allows the changing of unit
activation functions from within the training script. Thanks to
Thomas Rausch, University of Dresden, Germany.
- batchman output now with ``#'' prefix. This enables direct
processing by a lot of unix tools like gnuplot.
- batchman now automatically converts function parameters to
correct type instead of aborting.
- jogWeights can now also be called from batchman
- batchman catches some non-fatal signals (SIGINT, SIGTERM, ...)
and sets the internal variable SIGNAL so that the script can react
- batchman features ResetNet function (e.g. for Jordan networks).
- new tool ``linknets'' introduced to combine existing networks
- new tools ``td_bignet'' and ``ff_bignet'' introduced for
script-based generation of network files; Old tool bignet removed.
- displays will be refreshed more often when using the graphical editor
- weight and projection display with changed color scale. They now
match the 2D-display scale.
- pat_sel now can handle pattern files with multi-line comments
- manpages now available for most of the SNNS programs.
- the number of things stored in an xgui configuration file was
- Extensive debugging:
- batchman computes MSE now correctly from the number of (sub-)
- RBFs receive now correct number of parameters.
- spurious segmentation faults in the graphical editor tracked
- segmentation fault when training on huge pattern files
- various seg-faults under single operating systems tracked and cleared.
- netperf now can test on networks that need multiple training
- segmentaion faults when displaying 3D-Networks cleared.
- correct default values for initialization functions in
- the call ``TestNet()'' prohibited further training in
batchman. Now everything works as expected.
- segmentation fault in batchman when doing multiple string
concats cleared and memory leak in string operations
closed. Thanks to Walter Prins, University of Stellenbosch, South
- the output of the validation error on the shell window was
giving wrong values.
- algorithm SCG now respects special units and handles them
- the description of the learning function parameters in section
4.4 is finally ordered alphabetically.