Minimum description length (mdl) based training of a multilayer perceptron
(mlp) (feedforward neural network) with a single layer of hidden units. This
version uses a fixed number (3) hidden units. The motivation for
this learning is to control the amount of information in the weights
of the network. Like conventional "weight decay" it codes the network weight
under a prior Gaussian distribution, but takes into account not only the mean
of the "noisy" weights but also their variance. The details of the procedures
followed to generate the results in the archived are explained
here while the background is given in [1].
Software
The source is available as a compressed
tar file. However, be forewarned that this software was developed in
conjuction with xerion 3.1,
(not uts 4.0) an
old neural net simulator developed at the University of Toronto. While the
simulator is available free of charge, it may prove difficult to install.
Results
Directory listing of the results available for the
mlp-mdl-3h method. Put the desired files in the appropriate methods
directory in your delve hierarchy and uncompress them with using the
"gunzip *.gz" command and untar them using "tar -xvf
*.tar".