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In den WarenkorbZustand: New. KlappentextrnrnThe selection of salient features and an appropriate hidden layer architecture contributes significantly to the performance of a neural network. A number of metrics and methodologies exist for estimating these parameters. This res.
Sprache: Englisch
Verlag: British Library, Historical Print Editions Nov 2012, 2012
ISBN 10: 1288306814 ISBN 13: 9781288306817
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - The selection of salient features and an appropriate hidden layer architecture contributes significantly to the performance of a neural network. A number of metrics and methodologies exist for estimating these parameters. This research builds on recent efforts to integrate feature and architecture selection for the multi-layer perceptron. In the first stage of work a current algorithm is developed in a parallel environment, significantly improving its efficiency and utility. In the second stage, improvements to the algorithm are proposed. With regards to feature selection, a common random number (CRN) addition is presented. Two new methods of architecture selection are examined, including an information criterion and a signal-to-noise based procedure. These methodologies are shown to improve algorithm performance.