Bootstrap aggregating (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Bootstrap aggregating" in English language version.

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2semanticscholar.org

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2researchgate.net

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2corporatefinanceinstitute.com

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berkeley.edu (Global: 580^th place; English: 462^nd place)

stat.berkeley.edu

Breiman, Leo (September 1994). "Bagging Predictors" (PDF). Technical Report (421). Department of Statistics, University of California Berkeley. Retrieved 2019-07-28.
"Random forests - classification description". stat.berkeley.edu. Retrieved 2021-12-09.

corporatefinanceinstitute.com (Global: low place; English: 6,974^th place)

"Random Forest". Corporate Finance Institute. Retrieved 2021-11-26.
"What is Bagging (Bootstrap Aggregation)?". CFI. Corporate Finance Institute. Retrieved December 5, 2020.

doi.org (Global: 2^nd place; English: 2^nd place)

Breiman, Leo (1996). "Bagging predictors". Machine Learning. 24 (2): 123–140. CiteSeerX 10.1.1.32.9399. doi:10.1007/BF00058655. S2CID 47328136.
Bauer, Eric; Kohavi, Ron (1999). "An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants". Machine Learning. 36: 108–109. doi:10.1023/A:1007515423169. S2CID 1088806.
Efron, B. (1979). "Bootstrap methods: Another look at the jackknife". The Annals of Statistics. 7 (1): 1–26. doi:10.1214/aos/1176344552.

holypython.com (Global: low place; English: low place)

"Random Forest Pros & Cons". HolyPython.com. Retrieved 2021-11-26.

medium.com (Global: 551^st place; English: 406^th place)

dhirajkumarblog.medium.com

K, Dhiraj (2020-11-22). "Random Forest Algorithm Advantages and Disadvantages". Medium. Retrieved 2021-11-26.

medium.com

Zoghni, Raouf (September 5, 2020). "Bagging (Bootstrap Aggregating), Overview". The Startup – via Medium.

mit.edu (Global: 415^th place; English: 327^th place)

people.csail.mit.edu

Aslam, Javed A.; Popa, Raluca A.; and Rivest, Ronald L. (2007); On Estimating the Size and Confidence of a Statistical Audit, Proceedings of the Electronic Voting Technology Workshop (EVT '07), Boston, MA, August 6, 2007. More generally, when drawing with replacement $n'$ values out of a set of $n$ (different and equally likely), the expected number of unique draws is $n(1-e^{-n'/n})$ .

psu.edu (Global: 207^th place; English: 136^th place)

citeseerx.ist.psu.edu

Breiman, Leo (1996). "Bagging predictors". Machine Learning. 24 (2): 123–140. CiteSeerX 10.1.1.32.9399. doi:10.1007/BF00058655. S2CID 47328136.

researchgate.net (Global: 120^th place; English: 125^th place)

Sahu, A., Runger, G., Apley, D., Image denoising with a multi-phase kernel principal component approach and an ensemble version, IEEE Applied Imagery Pattern Recognition Workshop, pp.1-7, 2011.
Shinde, Amit, Anshuman Sahu, Daniel Apley, and George Runger. "Preimages for Variation Patterns from Kernel PCA and Bagging." IIE Transactions, Vol.46, Iss.5, 2014

section.io (Global: low place; English: low place)

"Introduction to Random Forest in Machine Learning". Engineering Education (EngEd) Program | Section. Retrieved 2021-12-09.

semanticscholar.org (Global: 11^th place; English: 8^th place)

api.semanticscholar.org

Breiman, Leo (1996). "Bagging predictors". Machine Learning. 24 (2): 123–140. CiteSeerX 10.1.1.32.9399. doi:10.1007/BF00058655. S2CID 47328136.
Bauer, Eric; Kohavi, Ron (1999). "An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants". Machine Learning. 36: 108–109. doi:10.1023/A:1007515423169. S2CID 1088806.

towardsai.net (Global: low place; English: low place)

Team, Towards AI (2 July 2020). "Why Choose Random Forest and Not Decision Trees – Towards AI – The World's Leading AI and Technology Publication". Retrieved 2021-11-26.