Daniel@0: Daniel@0: Daniel@0: Daniel@0: Netlab Reference Manual demmlp2 Daniel@0: Daniel@0: Daniel@0: Daniel@0:

demmlp2 Daniel@0:

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Daniel@0: Purpose Daniel@0:

Daniel@0: Demonstrate simple classification using a multi-layer perceptron Daniel@0: Daniel@0:

Daniel@0: Synopsis Daniel@0:

Daniel@0: 
Daniel@0: demmlp2
Daniel@0: Daniel@0: Daniel@0:

Daniel@0: Description Daniel@0:

Daniel@0: The problem consists of input data in two dimensions drawn from a mixture Daniel@0: of three Gaussians: two of which are assigned to a single class. An MLP Daniel@0: with logistic outputs trained with a quasi-Newton optimisation algorithm is Daniel@0: compared with the optimal Bayesian decision rule. Daniel@0: Daniel@0:

Daniel@0: See Also Daniel@0:

Daniel@0: mlp, mlpfwd, neterr, quasinew
Daniel@0: Pages: Daniel@0: Index Daniel@0:
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Copyright (c) Ian T Nabney (1996-9) Daniel@0: Daniel@0: Daniel@0: Daniel@0: