Method home for mlp-ese-1
This learning method trains ensembles of multilayer perceptrons using
early stopping. The networks all have identical architecture: fully
connected with a single hidden layer of hyperbolic tangent units and
linear output units. The minimisation algorithm is based on conjugate
gradients. Both hypertext
(generated by LaTeX2HTML) and postscript
descriptions of the algorithm are available. A detailed description of
the minimization procedure is available
in postscript.
Software
The source code for a C implementation (including the documentation) is
available as a compressed tar file.
Results
Directory listing of the results available for the
mlp-ese-1 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".
Related References
Last Updated by Carl Edward
Rasmussen, September 27, 1996