wolffd@0: wolffd@0: wolffd@0: wolffd@0: Netlab Reference Manual demmlp2 wolffd@0: wolffd@0: wolffd@0: wolffd@0:

demmlp2 wolffd@0:

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wolffd@0: Purpose wolffd@0:

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

wolffd@0: Synopsis wolffd@0:

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wolffd@0: demmlp2

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wolffd@0: Description wolffd@0:

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

wolffd@0: See Also wolffd@0:

wolffd@0: mlp, mlpfwd, neterr, quasinew

wolffd@0: Pages: wolffd@0: Index wolffd@0:

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