Method: mlp-wd-1

Mutilayer perceptron (feedforward neural) network with a single layer of hidden units, trained using weight decay as a regularizer on the weights. The motivation is to restrict overfitting by keeping the weights small. In conventional function fitting this method is called Ridge Regression and is a fairly standard text book forms of regularization [1]. The details of the procedure used to generate the results are reported here


The source is available as a compressed tar file. However, be forewarned that this source is not stand-alone. It runs within the neural net simulator Uts 4.1 developed at the University of Toronto. The simulator is available free of charge. You will first have to install it. The simulator will only run on UNIX like systems and requires Tcl, see the website for details. Only the Tcl scripts used for running the simulator are include in the tar file.


Directory listing of the results available for the mlp-wd-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

[1] C. M. Bishop. Neural networks for pattern recognition Oxford University Press 1995.
Last Updated 30 January 1998
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