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>
Keywords
Artificial intelligenceArtificial neural networkComputer scienceGeneralizationResidualMachine learningPattern recognition (psychology)MathematicsAlgorithm
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Publication Info
- Year
- 1990
- Type
- article
- Volume
- 12
- Issue
- 10
- Pages
- 993-1001
- Citations
- 4195
- Access
- Closed
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Cite This
Lars Kai Hansen,
Peter Salamon
(1990).
Neural network ensembles.
IEEE Transactions on Pattern Analysis and Machine Intelligence
, 12
(10)
, 993-1001.
https://doi.org/10.1109/34.58871
Identifiers
- DOI
- 10.1109/34.58871