The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Randomizing Outputs to Increase Prediction Accuracy
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Citations
Cites
Classification and Regression Trees.
Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,522
Self-citationClassification and Regression Trees.
Ryzin, J. V., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1986) · Journal of the American Statistical Association · doi:10.2307/2288003 · Cited by 20,825
Self-citationA decision-theoretic generalization of on-line learning and an application to boosting
Freund, Y., & Schapire, R. E. (1997) · Journal of Computer and System Sciences · doi:10.1006/jcss.1997.1504 · Cited by 20,466
Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325
Self-citationClassification And Regression Trees
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (2017) · doi:10.1201/9781315139470 · Cited by 11,417
Self-citationMultivariate Adaptive Regression Splines
Friedman, J. H. (1991) · The Annals of Statistics · doi:10.1214/aos/1176347963 · Cited by 8,000
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 1×
“To briefly review the work in Geman, Bienenstock, and Doursat (1992) and Breiman (1996a), we can always decompose Y as”
BackgroundDietterich, T. G. (2000) · Machine Learning · doi:10.1023/a:1007607513941 · Cited by 2,941
Heuristics of instability and stabilization in model selection
Breiman, L. (1996) · The Annals of Statistics · doi:10.1214/aos/1032181158 · Cited by 1,146
Self-citationArcing classifier (with discussion and a rejoinder by the author)
Breiman, L. (1998) · The Annals of Statistics · doi:10.1214/aos/1024691079 · Cited by 1,105
Self-citation
Cited by
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Self-citationGeurts, P., Ernst, D., & Wehenkel, L. (2006) · Machine Learning · doi:10.1007/s10994-006-6226-1 · Cited by 9,300
Biau, G., & Scornet, E. (2016) · Test · doi:10.1007/s11749-016-0481-7 · Cited by 4,149
Classification in the Presence of Label Noise: A Survey
Frenay, B., & Verleysen, M. (2014) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2013.2292894 · Cited by 1,777
Random Forests and Adaptive Nearest Neighbors
Lin, Y., & Jeon, Y. (2006) · Journal of the American Statistical Association · doi:10.1198/016214505000001230 · Cited by 507
Metadata
- Authors
- Breiman, L.
- Venue
- Machine Learning
- Published
- 2000-09
- Volume
- 40
- Issue
- 3
- Pages
- 229-242
- ISSN
- 0885-6125 (ISSN-L)
- 1573-0565
- OpenAlex
- W1580948147
- Cited by
- 276
- References
- 16
- FWCI
- 2.92
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Breiman, L. (2000). Randomizing Outputs to Increase Prediction Accuracy. Machine Learning. https://doi.org/10.1023/a%3A1007682208299
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
