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wolffd@0 1 <html>
wolffd@0 2 <head>
wolffd@0 3 <title>
wolffd@0 4 Netlab Reference Manual demmlp2
wolffd@0 5 </title>
wolffd@0 6 </head>
wolffd@0 7 <body>
wolffd@0 8 <H1> demmlp2
wolffd@0 9 </H1>
wolffd@0 10 <h2>
wolffd@0 11 Purpose
wolffd@0 12 </h2>
wolffd@0 13 Demonstrate simple classification using a multi-layer perceptron
wolffd@0 14
wolffd@0 15 <p><h2>
wolffd@0 16 Synopsis
wolffd@0 17 </h2>
wolffd@0 18 <PRE>
wolffd@0 19 demmlp2</PRE>
wolffd@0 20
wolffd@0 21
wolffd@0 22 <p><h2>
wolffd@0 23 Description
wolffd@0 24 </h2>
wolffd@0 25 The problem consists of input data in two dimensions drawn from a mixture
wolffd@0 26 of three Gaussians: two of which are assigned to a single class. An MLP
wolffd@0 27 with logistic outputs trained with a quasi-Newton optimisation algorithm is
wolffd@0 28 compared with the optimal Bayesian decision rule.
wolffd@0 29
wolffd@0 30 <p><h2>
wolffd@0 31 See Also
wolffd@0 32 </h2>
wolffd@0 33 <CODE><a href="mlp.htm">mlp</a></CODE>, <CODE><a href="mlpfwd.htm">mlpfwd</a></CODE>, <CODE><a href="neterr.htm">neterr</a></CODE>, <CODE><a href="quasinew.htm">quasinew</a></CODE><hr>
wolffd@0 34 <b>Pages:</b>
wolffd@0 35 <a href="index.htm">Index</a>
wolffd@0 36 <hr>
wolffd@0 37 <p>Copyright (c) Ian T Nabney (1996-9)
wolffd@0 38
wolffd@0 39
wolffd@0 40 </body>
wolffd@0 41 </html>