Who Cited It

Experiments with a new boosting algorithm

1996 · 7,582 citations · 30 from inside this corpus

Yoav Freund, Robert E. Schapire

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Experiments with a new boosting algorithm (1996)Experiments with a new boosti…C4.5: Programs for Machine Learning (1992)C4.5: Programs for Machine Le…Bagging Predictors (1996)Bagging PredictorsFast Effective Rule Induction (1995)Fast Effective Rule InductionThe Strength of Weak Learnability (1990)The Strength of Weak Learnabi…Boosting a Weak Learning Algorithm by Majority (1995)Boosting a Weak Learning Algo…Random Forests (2001)Random ForestsGreedy function approximation: A gradient boosting machine. (2001)Greedy function approximation…Extreme learning machine: Theory and applications (2006)Extreme learning machine: The…Learning from Imbalanced Data (2009)Learning from Imbalanced DataEnsemble Methods in Machine Learning (2000)Ensemble Methods in Machine L…The random subspace method for constructing decision forests (1998)The random subspace method fo…Pattern Recognition and Neural Networks (1996)Pattern Recognition and Neura…Machine Learning: Algorithms, Real-World Applications and Research Directions (2021)Machine Learning: Algorithms,…On combining classifiers (1998)On combining classifiersLearning Deep Architectures for AI (2009)Learning Deep Architectures f…ADASYN: Adaptive synthetic sampling approach for imbalanced learning (2008)ADASYN: Adaptive synthetic sa…Extreme learning machine: a new learning scheme of feedforward neural networks (2005)Extreme learning machine: a n…Popular Ensemble Methods: An Empirical Study (1999)Popular Ensemble Methods: An …An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:… (2000)An Experimental Comparison of…A Short Introduction to Boosting (1999)A Short Introduction to Boost…An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia… (1999)An Empirical Comparison of Vo…Improved boosting algorithms using confidence-rated predictions (1998)Learning from class-imbalanced data: Review of methods and applications (2016)Learning from class-imbalance…Boosting the margin: a new explanation for the effectiveness of voting methods (1998)Boosting the margin: a new ex…BoosTexter: A Boosting-based System for Text Categorization (2000)BoosTexter: A Boosting-based …Ensemble deep learning: A review (2022)Ensemble deep learning: A rev…The Boosting Approach to Machine Learning: An Overview (2003)The Boosting Approach to Mach…Ensembling neural networks: Many could be better than all (2002)Ensembling neural networks: M…Improved Boosting Algorithms Using Confidence-rated Predictions (1999)Improved Boosting Algorithms …RUSBoost: A Hybrid Approach to Alleviating Class Imbalance (2009)RUSBoost: A Hybrid Approach t…Classification in the Presence of Label Noise: A Survey (2014)Classification in the Presenc…SMOTEBoost: Improving Prediction of the Minority Class in Boosting (2003)SMOTEBoost: Improving Predict…Kernel methods in machine learning (2008)Kernel methods in machine lea…Support vector machines for spam categorization (1999)Support vector machines for s…Cost-sensitive boosting for classification of imbalanced data (2007)
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What this paper cites, inside the corpus

PaperYearCited
C4.5: Programs for Machine Learning199223,704
Bagging Predictors199617,191
Fast Effective Rule Induction19953,810
The Strength of Weak Learnability19903,344
Boosting a Weak Learning Algorithm by Majority19951,691

What cites it, inside the corpus

PaperYearCited
Random Forests2001131,109
Greedy function approximation: A gradient boosting machine.200130,137
Extreme learning machine: Theory and applications200613,310
Learning from Imbalanced Data200910,209
Ensemble Methods in Machine Learning20008,058
The random subspace method for constructing decision forests19986,904
Pattern Recognition and Neural Networks19966,514
Machine Learning: Algorithms, Real-World Applications and Research Directions20215,368
On combining classifiers19985,302
Learning Deep Architectures for AI20095,077
ADASYN: Adaptive synthetic sampling approach for imbalanced learning20084,556
Extreme learning machine: a new learning scheme of feedforward neural networks20054,122
Popular Ensemble Methods: An Empirical Study19992,988
An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…20002,962
A Short Introduction to Boosting19992,952
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…19992,656
Improved boosting algorithms using confidence-rated predictions19982,573
Learning from class-imbalanced data: Review of methods and applications20162,407
Boosting the margin: a new explanation for the effectiveness of voting methods19982,344
BoosTexter: A Boosting-based System for Text Categorization20002,200
Ensemble deep learning: A review20222,136
The Boosting Approach to Machine Learning: An Overview20032,023
Ensembling neural networks: Many could be better than all20021,990
Improved Boosting Algorithms Using Confidence-rated Predictions19991,966
RUSBoost: A Hybrid Approach to Alleviating Class Imbalance20091,890
Classification in the Presence of Label Noise: A Survey20141,777
SMOTEBoost: Improving Prediction of the Minority Class in Boosting20031,680
Kernel methods in machine learning20081,618
Support vector machines for spam categorization19991,480
Cost-sensitive boosting for classification of imbalanced data20071,438

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Topics

Machine Learning and Data ClassificationComputer Science
Machine Learning and AlgorithmsComputer Science
Imbalanced Data Classification TechniquesComputer Science

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complete

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  • supports2 author record(s) attached.
  • supports19 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:43+00:00.

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