Neural network ensembles

19904,231 citationsJournal Article

Authors

Lars Kai Hansen · San Diego State University

Peter Salamon · San Diego State University

Abstract

Several means for improving the performance and training of neural networks for classification are proposed. Crossvalidation is used as a tool for optimizing network parameters and architecture. It is shown that the remaining residual generalization error can be reduced by invoking ensembles of similar networks.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

Topics & Keywords

Neural Networks and Applications Face and Expression Recognition Fault Detection and Control Systems

Publication Details

Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence

Volume 12, Issue 10, pp. 993-1001

DOI: 10.1109/34.58871

Field-Weighted Citation Impact: 7.53

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Neural network ensembles

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Abstract

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Publication Details