1998 | OriginalPaper | Buchkapitel
Geometrical Selection of Important Inputs with Feedforward Neural Networks
verfasst von : F. Rossi
Erschienen in: Artificial Neural Nets and Genetic Algorithms
Verlag: Springer Vienna
Enthalten in: Professional Book Archive
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In this paper, we introduce a method that allows to evaluate efficiently the ‘importance’ of each coordinate of the input vector of a neural network. This measurement can be used to obtain information about the studied data. It can also be used to suppress irrelevant inputs in order to speed up the classification process conducted by the network.