The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Generalization error of ensemble estimators
Abstract
It has been empirically shown that a better estimate with less generalization error can be obtained by averaging outputs of multiple estimators. This paper presents an analytical result for the generalization error of ensemble estimators. First, we derive a general expression of the ensemble generalization error by using factors of interest (bias, variance, covariance, and noise variance) and show how the generalization error is affected by each of them. Some special cases are then investigated. The result of a simulation is shown to verify our analytical result. A practically important problem of the ensemble approach, ensemble dilemma, is also discussed.
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Cites
Wolpert, D. H. (1992) · Neural Networks · doi:10.1016/s0893-6080(05)80023-1 · Cited by 7,951
Hansen, L. K., & Salamon, P. (1990) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.58871 · Cited by 4,260
Neural Networks and the Bias/Variance Dilemma
Geman, S., Bienenstock, E., & Doursat, R. (1992) · Neural Computation · doi:10.1162/neco.1992.4.1.1 · Cited by 3,578
Cited by
Ensemble approaches for regression: A survey
Mendes-Moreira, J., Soares, C., Jorge, A. M., & Sousa, J. F. D. (2012) · ACM Computing Surveys · doi:10.1145/2379776.2379786 · Cited by 667
Exploring the Transferability of Visual Prompting for Multimodal Large Language Models
Zhang, Y., Dong, Y., Zhang, S., Min, T., Su, H., & Zhu, J. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52733.2024.02508 · Cited by 17
Metadata
- Authors
- Ueda, N., & Nakano, R.
- Venue
- Proceedings of International Conference on Neural Networks (ICNN'96)
- Publisher
- IEEE
- Published
- 2002-12-24
- Volume
- 1
- Pages
- 90-95
- OpenAlex
- W2158875652
- Cited by
- 230
- References
- 3
- FWCI
- 6.25
- Type
- conference paper
- Language
- en
- Open access
- closed
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