Who Cited It

Ensemble learning: A survey

2018 · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · 3,088 citations · 2 from inside this corpus

Omer Sagi low, Lior Rokach

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.

Ensemble learning: A survey (2018)Ensemble learning: A surveyRandom Forests (2001)Random ForestsXGBoost (2016)XGBoostDropout: a simple way to prevent neural networks from overfitting (2014)Dropout: a simple way to prev…Greedy function approximation: A gradient boosting machine. (2001)Greedy function approximation…Bagging predictors (1996)Bagging predictorsExtremely randomized trees (2006)Extremely randomized treesStacked generalization (1992)Stacked generalizationThe random subspace method for constructing decision forests (1998)The random subspace method fo…Adaptive Mixtures of Local Experts (1991)Adaptive Mixtures of Local Ex…Neural network ensembles (1990)Neural network ensemblesGradient boosting machines, a tutorial (2013)Gradient boosting machines, a…The class imbalance problem: A systematic study1 (2002)The class imbalance problem: …Popular Ensemble Methods: An Empirical Study (1999)Popular Ensemble Methods: An …Combining Pattern Classifiers (2004)Combining Pattern ClassifiersEnsemble based systems in decision making (2006)Ensemble based systems in dec…An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:… (2000)An Experimental Comparison of…A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Ba… (2011)A Review on Ensembles for the…Solving Multiclass Learning Problems via Error-Correcting Output Codes (1995)Solving Multiclass Learning P…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)Improved boosting algorithms …The strength of weak learnability (1990)The strength of weak learnabi…Model compression (2006)Model compressionEnsembling neural networks: Many could be better than all (2002)Ensembling neural networks: M…Rotation Forest: A New Classifier Ensemble Method (2006)Rotation Forest: A New Classi…Ensemble deep learning: A review (2022)Ensemble deep learning: A rev…CatBoost for big data: an interdisciplinary review (2020)CatBoost for big data: an int…
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What this paper cites, inside the corpus

PaperYearCited
Random Forests2001131,109
XGBoost201652,304
Dropout: a simple way to prevent neural networks from overfitting201434,236
Greedy function approximation: A gradient boosting machine.200130,137
Bagging predictors199616,468
Extremely randomized trees20069,068
Stacked generalization19927,777
The random subspace method for constructing decision forests19986,904
Adaptive Mixtures of Local Experts19915,234
Neural network ensembles19904,288
Gradient boosting machines, a tutorial20133,896
The class imbalance problem: A systematic study120023,353
Popular Ensemble Methods: An Empirical Study19992,988
Combining Pattern Classifiers20042,980
Ensemble based systems in decision making20062,965
An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…20002,962
A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Ba…20112,834
Solving Multiclass Learning Problems via Error-Correcting Output Codes19952,729
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…19992,656
Improved boosting algorithms using confidence-rated predictions19982,573
The strength of weak learnability19902,477
Model compression20062,118
Ensembling neural networks: Many could be better than all20021,990
Rotation Forest: A New Classifier Ensemble Method20061,911

What cites it, inside the corpus

PaperYearCited
Ensemble deep learning: A review20222,136
CatBoost for big data: an interdisciplinary review20201,776

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Topics

Data Stream Mining TechniquesComputer Science
Anomaly Detection Techniques and ApplicationsComputer Science
Time Series Analysis and ForecastingComputer Science

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complete

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  • supports2 author record(s) attached.
  • supports146 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

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