Who Cited It

Bagging Predictors

1996 · Machine Learning · 17,191 citations · 41 from inside this corpus

Leo Breiman

No abstract in the source record.

Bagging Predictors (1996)Bagging PredictorsAn Introduction to the Bootstrap (1993)An Introduction to the Bootst…Machine Learning, Neural and Statistical Classification (1995)Machine Learning, Neural and …Random Forests (2001)Random ForestsDeep learning in neural networks: An overview (2014)Deep learning in neural netwo…Extremely randomized trees (2006)Extremely randomized treesWrappers for feature subset selection (1997)Wrappers for feature subset s…Ensemble Methods in Machine Learning (2000)Ensemble Methods in Machine L…Experiments with a new boosting algorithm (1996)Experiments with a new boosti…The random subspace method for constructing decision forests (1998)The random subspace method fo…Improving neural networks by preventing co-adaptation of feature detectors (2012)Improving neural networks by …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 classifiersActive Learning Literature Survey (2009)Active Learning Literature Su…Semi-Supervised Learning (2006)Semi-Supervised LearningSupervised Machine Learning: A Review of Classification Techniques (2007)Supervised Machine Learning: …A random forest guided tour (2016)A random forest guided tourApproximate Statistical Tests for Comparing Supervised Classification Learning Algorithms (1998)Approximate Statistical Tests…Machine Learning in Medicine (2015)Machine Learning in MedicinePopular Ensemble Methods: An Empirical Study (1999)Popular Ensemble Methods: An …Ensemble 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…An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia… (1999)An Empirical Comparison of Vo…Variable selection using random forests (2010)Variable selection using rand…Exploratory Undersampling for Class-Imbalance Learning (2008)Exploratory Undersampling for…Boosting the margin: a new explanation for the effectiveness of voting methods (1998)Boosting the margin: a new ex…Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Ac… (2003)Measures of Diversity in Clas…Classifier chains for multi-label classification (2011)Classifier chains for multi-l…Ensemble deep learning: A review (2022)Ensemble deep learning: A rev…Model compression (2006)Model compressionEnsembling neural networks: Many could be better than all (2002)Practical Recommendations for Gradient-Based Training of Deep Architectures (2012)Practical Recommendations for…A survey on ensemble learning (2019)A survey on ensemble learningExtreme learning machines: a survey (2011)Extreme learning machines: a …Multi-class AdaBoost (2009)Multi-class AdaBoost
36 of 38 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
An Introduction to the Bootstrap199321,041
Machine Learning, Neural and Statistical Classification19952,193

What cites it, inside the corpus

PaperYearCited
Random Forests2001131,109
Deep learning in neural networks: An overview201418,236
Extremely randomized trees20069,068
Wrappers for feature subset selection19978,991
Ensemble Methods in Machine Learning20008,058
Experiments with a new boosting algorithm19967,582
The random subspace method for constructing decision forests19986,904
Improving neural networks by preventing co-adaptation of feature detectors20126,653
Pattern Recognition and Neural Networks19966,514
Machine Learning: Algorithms, Real-World Applications and Research Directions20215,368
On combining classifiers19985,302
Active Learning Literature Survey20094,788
Semi-Supervised Learning20064,334
Supervised Machine Learning: A Review of Classification Techniques20074,149
A random forest guided tour20164,026
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms19983,759
Machine Learning in Medicine20153,534
Popular Ensemble Methods: An Empirical Study19992,988
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
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…19992,656
Variable selection using random forests20102,615
Exploratory Undersampling for Class-Imbalance Learning20082,504
Boosting the margin: a new explanation for the effectiveness of voting methods19982,344
Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Ac…20032,321
Classifier chains for multi-label classification20112,307
Ensemble deep learning: A review20222,136
Model compression20062,118
Ensembling neural networks: Many could be better than all20021,990
Practical Recommendations for Gradient-Based Training of Deep Architectures20121,960
A survey on ensemble learning20191,951
Extreme learning machines: a survey20111,932
Multi-class AdaBoost20091,916

Links

DOI · Open access copy · OpenAlex record

Topics

Neural Networks and ApplicationsComputer Science
Data Mining Algorithms and ApplicationsComputer Science

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complete

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  • supports1 author record(s) attached.
  • supports16 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

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