articleTop 10% cited

Neural network ensembles

IEEE Transactions on Pattern Analysis and Machine Intelligence · 1990 · Vol. 12(10) · pp. 993–1001

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>

Neural Networks and Applications Face and Expression Recognition Fault Detection and Control SystemsArtificial intelligenceArtificial neural networkComputer scienceGeneralizationResidualMachine learningPattern recognition (psychology)MathematicsAlgorithm

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A Survey of Ensemble Learning: Concepts, Algorithms, Applications, and Prospects