提升方法 (Chinese Wikipedia)
Analysis of information sources in references of the Wikipedia article "提升方法" in Chinese language version.
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archive.org
- Leo Breiman. Arcing classifier (with discussion and a rejoinder by the author). Ann. Stat. 1998, 26 (3): 801–849. doi:10.1214/aos/1024691079
. Schapire (1990) proved that boosting is possible. (Page 823)
berkeley.edu
oz.berkeley.edu
- Leo Breiman. BIAS, VARIANCE, AND ARCING CLASSIFIERS (PDF). TECHNICAL REPORT. 1996 [19 January 2015]. （原始内容 (PDF)存档于2015-01-19）.
Arcing [Boosting] is more successful than bagging in variance reduction
doi.org
- Schapire, Robert E. The Strength of Weak Learnability (PDF). Machine Learning. 1990, 5 (2): 197–227 [2012-08-23]. CiteSeerX 10.1.1.20.723 . S2CID 53304535. doi:10.1007/bf00116037. （原始内容 (PDF)存档于2012-10-10）.
- Leo Breiman. Arcing classifier (with discussion and a rejoinder by the author). Ann. Stat. 1998, 26 (3): 801–849. doi:10.1214/aos/1024691079 .
Schapire (1990) proved that boosting is possible. (Page 823)
phillong.info
- Philip M. Long, Rocco A. Servedio, "Random Classification Noise Defeats All Convex Potential Boosters" (PDF). [2014-04-17]. （原始内容存档 (PDF)于2021-01-18）.
princeton.edu
cs.princeton.edu
- Schapire, Robert E. The Strength of Weak Learnability (PDF). Machine Learning. 1990, 5 (2): 197–227 [2012-08-23]. CiteSeerX 10.1.1.20.723 . S2CID 53304535. doi:10.1007/bf00116037. （原始内容 (PDF)存档于2012-10-10）.
psu.edu
citeseerx.ist.psu.edu
- Schapire, Robert E. The Strength of Weak Learnability (PDF). Machine Learning. 1990, 5 (2): 197–227 [2012-08-23]. CiteSeerX 10.1.1.20.723 . S2CID 53304535. doi:10.1007/bf00116037. （原始内容 (PDF)存档于2012-10-10）.
semanticscholar.org
api.semanticscholar.org
- Schapire, Robert E. The Strength of Weak Learnability (PDF). Machine Learning. 1990, 5 (2): 197–227 [2012-08-23]. CiteSeerX 10.1.1.20.723 . S2CID 53304535. doi:10.1007/bf00116037. （原始内容 (PDF)存档于2012-10-10）.
upenn.edu
cis.upenn.edu
- Michael Kearns (1988); Thoughts on Hypothesis Boosting （页面存档备份，存于互联网档案馆）, Unpublished manuscript (Machine Learning class project, December 1988)
web.archive.org
- Leo Breiman. BIAS, VARIANCE, AND ARCING CLASSIFIERS (PDF). TECHNICAL REPORT. 1996 [19 January 2015]. （原始内容 (PDF)存档于2015-01-19）.
Arcing [Boosting] is more successful than bagging in variance reduction
- Michael Kearns (1988); Thoughts on Hypothesis Boosting （页面存档备份，存于互联网档案馆）, Unpublished manuscript (Machine Learning class project, December 1988)
- Schapire, Robert E. The Strength of Weak Learnability (PDF). Machine Learning. 1990, 5 (2): 197–227 [2012-08-23]. CiteSeerX 10.1.1.20.723 . S2CID 53304535. doi:10.1007/bf00116037. （原始内容 (PDF)存档于2012-10-10）.
- Philip M. Long, Rocco A. Servedio, "Random Classification Noise Defeats All Convex Potential Boosters" (PDF). [2014-04-17]. （原始内容存档 (PDF)于2021-01-18）.