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- Boosting_(machine_learning) abstract "Boosting is a machine learning meta-algorithm for reducing bias in supervised learning. Boosting is based on the question posed by Kearns: Can a set of weak learners create a single strong learner? A weak learner is defined to be a classifier which is only slightly correlated with the true classification (it can label examples better than random guessing). In contrast, a strong learner is a classifier that is arbitrarily well-correlated with the true classification.Schapire's affirmative answer to Kearns' question has had significant ramifications in machine learning and statistics, most notably leading to the development of boosting.When first introduced, the hypothesis boosting problem simply referred to the process of turning a weak learner into a strong learner. "Informally, [the hypothesis boosting] problem asks whether an efficient learning algorithm […] that outputs a hypothesis whose performance is only slightly better than random guessing [i.e. a weak learner] implies the existence of an efficient algorithm that outputs an hypothesis of arbitrary accuracy [i.e. a strong learner]." Algorithms that achieve hypothesis boosting quickly became simply known as "boosting". Freund and Schapire's arcing (Adapt[at]ive Resampling and Combining), as a general technique, is more or less synonymous with boosting.".
- Boosting_(machine_learning) wikiPageExternalLink schapire99improved.html.
- Boosting_(machine_learning) wikiPageExternalLink index.html.
- Boosting_(machine_learning) wikiPageExternalLink Orange.ensemble.
- Boosting_(machine_learning) wikiPageExternalLink Schapire2003.pdf.
- Boosting_(machine_learning) wikiPageExternalLink boost.html.
- Boosting_(machine_learning) wikiPageExternalLink adaboost.pdf.
- Boosting_(machine_learning) wikiPageExternalLink LS10_potential.pdf.
- Boosting_(machine_learning) wikiPageID "90500".
- Boosting_(machine_learning) wikiPageRevisionID "605916249".
- Boosting_(machine_learning) hasPhotoCollection Boosting_(machine_learning).
- Boosting_(machine_learning) subject Category:Classification_algorithms.
- Boosting_(machine_learning) subject Category:Ensemble_learning.
- Boosting_(machine_learning) comment "Boosting is a machine learning meta-algorithm for reducing bias in supervised learning. Boosting is based on the question posed by Kearns: Can a set of weak learners create a single strong learner? A weak learner is defined to be a classifier which is only slightly correlated with the true classification (it can label examples better than random guessing).".
- Boosting_(machine_learning) label "Boosting (machine learning)".
- Boosting_(machine_learning) label "Boosting".
- Boosting_(machine_learning) label "Boosting".
- Boosting_(machine_learning) label "ブースティング".
- Boosting_(machine_learning) label "提升方法".
- Boosting_(machine_learning) sameAs Boosting.
- Boosting_(machine_learning) sameAs Boosting.
- Boosting_(machine_learning) sameAs ブースティング.
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- Boosting_(machine_learning) sameAs Q466303.
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- Boosting_(machine_learning) wasDerivedFrom Boosting_(machine_learning)?oldid=605916249.
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