梯度提升技术 (Chinese Wikipedia)

Analysis of information sources in references of the Wikipedia article "梯度提升技术" in Chinese language version.

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13web.archive.org

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2stanford.edu

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2r-project.org

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2nih.gov

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2doi.org

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1berkeley.edu

580^th place

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1nips.cc

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1dur.ac.uk

3,728^th place

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1chengli.io

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1su.domains

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1analyticsvidhya.com

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1washington.edu

1,067^th place

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1rutgers.edu

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1ya.ru

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1archive.org

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analyticsvidhya.com

Learn Gradient Boosting Algorithm for better predictions (with codes in R). [2019-11-12]. （原始内容存档于2019-08-13）.

archive.org

Elith, Jane. A working guide to boosted regression trees. Journal of Animal Ecology. 2008, 77 (4): 802–813. PMID 18397250. doi:10.1111/j.1365-2656.2008.01390.x.

berkeley.edu

statistics.berkeley.edu

Breiman, L. Arcing The Edge (PDF). Statistics Department, University of California, Berkeley. June 1997 [2019-11-12]. （原始内容存档 (PDF)于2020-05-09）.

chengli.io

Cheng Li. A Gentle Introduction to Gradient Boosting (PDF). [2019-11-12]. （原始内容存档 (PDF)于2018-10-24）.

doi.org

Friedman, Jerome. Multiple Additive Regression Trees with Application in Epidemiology. Statistics in Medicine. 2003, 22 (9): 1365–1381. PMID 12704603. doi:10.1002/sim.1501.
Elith, Jane. A working guide to boosted regression trees. Journal of Animal Ecology. 2008, 77 (4): 802–813. PMID 18397250. doi:10.1111/j.1365-2656.2008.01390.x.

dur.ac.uk

maths.dur.ac.uk

Mason, L.; Baxter, J.; Bartlett, P. L.; Frean, Marcus. Boosting Algorithms as Gradient Descent in Function Space (PDF). May 1999 [2019-11-12]. （原始内容 (PDF)存档于2018-12-22）.

nih.gov

ncbi.nlm.nih.gov

Friedman, Jerome. Multiple Additive Regression Trees with Application in Epidemiology. Statistics in Medicine. 2003, 22 (9): 1365–1381. PMID 12704603. doi:10.1002/sim.1501.
Elith, Jane. A working guide to boosted regression trees. Journal of Animal Ecology. 2008, 77 (4): 802–813. PMID 18397250. doi:10.1111/j.1365-2656.2008.01390.x.

nips.cc

papers.nips.cc

Mason, L.; Baxter, J.; Bartlett, P. L.; Frean, Marcus. Boosting Algorithms as Gradient Descent (PDF). S.A. Solla and T.K. Leen and K. Müller (编). Advances in Neural Information Processing Systems 12. MIT Press: 512–518. 1999 [2022-09-10]. （原始内容存档 (PDF)于2019-12-22）.

r-project.org

cran.r-project.org

Ridgeway, Greg. Generalized Boosted Models: A guide to the gbm package (PDF). 2007. （原始内容存档 (PDF)于2020-02-10）.
Elith, Jane. Boosted Regression Trees for ecological modeling (PDF). CRAN. CRAN. [31 August 2018]. （原始内容存档 (PDF)于2020-07-25）.

rutgers.edu

stat.rutgers.edu

Cossock, David and Zhang, Tong (2008). Statistical Analysis of Bayes Optimal Subset Ranking 互联网档案馆的存檔，存档日期2010-08-07., page 14.

stanford.edu

statweb.stanford.edu

Friedman, J. H. Greedy Function Approximation: A Gradient Boosting Machine (PDF). February 1999 [2019-11-12]. （原始内容存档 (PDF)于2019-11-01）.
Friedman, J. H. Stochastic Gradient Boosting (PDF). March 1999 [2019-11-12]. （原始内容存档 (PDF)于2014-08-01）.

su.domains

hastie.su.domains

Hastie, T.; Tibshirani, R.; Friedman, J. H. 10. Boosting and Additive Trees. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd. New York: Springer. 2009: 337–384. ISBN 978-0-387-84857-0. （原始内容存档于2009-11-10）.

washington.edu

homes.cs.washington.edu

Tianqi Chen. Introduction to Boosted Trees （页面存档备份，存于互联网档案馆）

web.archive.org

Breiman, L. Arcing The Edge (PDF). Statistics Department, University of California, Berkeley. June 1997 [2019-11-12]. （原始内容存档 (PDF)于2020-05-09）.
Friedman, J. H. Greedy Function Approximation: A Gradient Boosting Machine (PDF). February 1999 [2019-11-12]. （原始内容存档 (PDF)于2019-11-01）.
Friedman, J. H. Stochastic Gradient Boosting (PDF). March 1999 [2019-11-12]. （原始内容存档 (PDF)于2014-08-01）.
Mason, L.; Baxter, J.; Bartlett, P. L.; Frean, Marcus. Boosting Algorithms as Gradient Descent (PDF). S.A. Solla and T.K. Leen and K. Müller (编). Advances in Neural Information Processing Systems 12. MIT Press: 512–518. 1999 [2022-09-10]. （原始内容存档 (PDF)于2019-12-22）.
Mason, L.; Baxter, J.; Bartlett, P. L.; Frean, Marcus. Boosting Algorithms as Gradient Descent in Function Space (PDF). May 1999 [2019-11-12]. （原始内容 (PDF)存档于2018-12-22）.
Cheng Li. A Gentle Introduction to Gradient Boosting (PDF). [2019-11-12]. （原始内容存档 (PDF)于2018-10-24）.
Hastie, T.; Tibshirani, R.; Friedman, J. H. 10. Boosting and Additive Trees. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd. New York: Springer. 2009: 337–384. ISBN 978-0-387-84857-0. （原始内容存档于2009-11-10）.
Ridgeway, Greg. Generalized Boosted Models: A guide to the gbm package (PDF). 2007. （原始内容存档 (PDF)于2020-02-10）.
Learn Gradient Boosting Algorithm for better predictions (with codes in R). [2019-11-12]. （原始内容存档于2019-08-13）.
Tianqi Chen. Introduction to Boosted Trees （页面存档备份，存于互联网档案馆）
Cossock, David and Zhang, Tong (2008). Statistical Analysis of Bayes Optimal Subset Ranking 互联网档案馆的存檔，存档日期2010-08-07., page 14.
Yandex corporate blog entry about new ranking model "Snezhinsk" （页面存档备份，存于互联网档案馆） (in Russian)
Elith, Jane. Boosted Regression Trees for ecological modeling (PDF). CRAN. CRAN. [31 August 2018]. （原始内容存档 (PDF)于2020-07-25）.

ya.ru

webmaster.ya.ru

Yandex corporate blog entry about new ranking model "Snezhinsk" （页面存档备份，存于互联网档案馆） (in Russian)