Daniel@0: Daniel@0: Daniel@0: Daniel@0: Netlab Reference Manual demtrain Daniel@0: Daniel@0: Daniel@0: Daniel@0:

demtrain Daniel@0:

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Daniel@0: Purpose Daniel@0:

Daniel@0: Demonstrate training of MLP network. Daniel@0: Daniel@0:

Daniel@0: Synopsis Daniel@0:

Daniel@0: 
Daniel@0: demtrain
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Daniel@0: Description Daniel@0:

Daniel@0: demtrain brings up a simple GUI to show the training of Daniel@0: an MLP network on classification and regression problems. The user Daniel@0: should load in a dataset (which should be in Netlab format: see Daniel@0: datread), select the output activation function, the Daniel@0: number of cycles and hidden units and then Daniel@0: train the network. The scaled conjugate gradient algorithm is used. Daniel@0: A graph shows the evolution of the error: the value is shown Daniel@0: max(ceil(iterations / 50), 5) cycles. Daniel@0: Daniel@0:

Once the network is trained, it is saved to the file mlptrain.net. Daniel@0: The results can then be viewed as a confusion matrix (for classification Daniel@0: problems) or a plot of output versus target (for regression problems). Daniel@0: Daniel@0:

Daniel@0: See Also Daniel@0:

Daniel@0: confmat, datread, mlp, netopt, scg
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: