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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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<html> <head> <title> Netlab Reference Manual demtrain </title> </head> <body> <H1> demtrain </H1> <h2> Purpose </h2> Demonstrate training of MLP network. <p><h2> Synopsis </h2> <PRE> demtrain</PRE> <p><h2> Description </h2> <CODE>demtrain</CODE> brings up a simple GUI to show the training of an MLP network on classification and regression problems. The user should load in a dataset (which should be in Netlab format: see <CODE>datread</CODE>), select the output activation function, the number of cycles and hidden units and then train the network. The scaled conjugate gradient algorithm is used. A graph shows the evolution of the error: the value is shown <CODE>max(ceil(iterations / 50), 5)</CODE> cycles. <p>Once the network is trained, it is saved to the file <CODE>mlptrain.net</CODE>. The results can then be viewed as a confusion matrix (for classification problems) or a plot of output versus target (for regression problems). <p><h2> See Also </h2> <CODE><a href="confmat.htm">confmat</a></CODE>, <CODE><a href="datread.htm">datread</a></CODE>, <CODE><a href="mlp.htm">mlp</a></CODE>, <CODE><a href="netopt.htm">netopt</a></CODE>, <CODE><a href="scg.htm">scg</a></CODE><hr> <b>Pages:</b> <a href="index.htm">Index</a> <hr> <p>Copyright (c) Ian T Nabney (1996-9) </body> </html>