Titlebook: Neural Networks and the Financial Markets; Predicting, Combinin Jimmy Shadbolt,John G. Taylor Book 2002 Springer-Verlag London 2002 Arbitra

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Neural Networksprogramming in the required responses of the network to inputs from the environment. This feature is very important, since a neural network can thereby be trained to give a desired response to a set of inputs even though there are no explicit rules for this response to be achieved.

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ESO

Input Selection the limitations in the method described below. We also note that before we get to this stage we will have been through a data reduction stage using, for example, the PCA techniques described earlier.

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Incise

Vector Machines inner product is reduced to the evaluation of a suitable kernel at the two original data values: .. The non-linear mapping: . → φ(.) leads to an extension of non-linear regression by this higher dimensional embedding method.