The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Combining Estimates in Regression and Classification
Abstract
We consider the problem of how to combine a collection of general regression fit vectors to obtain a better predictive model. The individual fits may be from subset linear regression, ridge regression, or something more complex like a neural network. We develop a general framework for this problem and examine a cross-validation—based proposal called “model mix” or “stacking” in this context. We also derive combination methods based on the bootstrap and analytic methods and compare them in examples. Finally, we apply these ideas to classification problems where the estimated combination weights can yield insight into the structure of the problem.
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Cites
Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325
Wolpert, D. H. (1992) · Neural Networks · doi:10.1016/s0893-6080(05)80023-1 · Cited by 7,951
Solving Least Squares Problems
Lawson, C. L., & Hanson, R. J. (1995) · doi:10.1137/1.9781611971217 · Cited by 7,103
Cited by
Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00117832 · Cited by 1,912
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
Metadata
- Authors
- Leblanc, M., & Tibshirani, R.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1996-12
- Volume
- 91
- Issue
- 436
- Pages
- 1641-1650
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W1990322717
- Cited by
- 290
- References
- 3
- FWCI
- 9.90
- Type
- journal article
- Language
- en
- Open access
- closed
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- Leblanc, M., & Tibshirani, R. (1996). Combining Estimates in Regression and Classification. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1996.10476733
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