An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants

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• Random Forests→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Extremely randomized trees→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Ensemble Methods in Machine Learning→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• A study of the behavior of several methods for balancing machine learning training data→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• A few useful things to know about machine learning→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Ensemble learning: A survey→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Popular Ensemble Methods: An Empirical Study→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Ensemble based systems in decision making→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• A Short Introduction to Boosting→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Improved boosting algorithms using confidence-rated predictions→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Exploratory Undersampling for Class-Imbalance Learning→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Ac…→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Ensembling neural networks: Many could be better than all→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Improved Boosting Algorithms Using Confidence-rated Predictions→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• The foundations of cost-sensitive learning→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Machine learning: a review of classification and combining techniques→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→An Introduction to the BootstrapLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→Bagging PredictorsLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model SelectionLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→Stacked generalizationLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→Approximate Statistical Tests for Comparing Supervised Classification Learning AlgorithmsLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→Neural Networks and the Bias/Variance DilemmaLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→The Strength of Weak LearnabilityLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→On the Optimality of the Simple Bayesian Classifier under Zero-One LossLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→Bayesian TheoryLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→Boosting a Weak Learning Algorithm by MajorityLegacy edge — source detail unavailable
• Ensemble Methods in Machine Learning→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• Ensemble Methods in Machine Learning→Improved boosting algorithms using confidence-rated predictionsLegacy edge — source detail unavailable
• Ensemble Methods in Machine Learning→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• Ensemble Methods in Machine Learning→Bagging PredictorsLegacy edge — source detail unavailable
• An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…→Approximate Statistical Tests for Comparing Supervised Classification Learning AlgorithmsLegacy edge — source detail unavailable
• An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…→Bagging PredictorsLegacy edge — source detail unavailable
• A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection→Stacked generalizationLegacy edge — source detail unavailable
• Boosting the margin: a new explanation for the effectiveness of voting methods→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• Boosting the margin: a new explanation for the effectiveness of voting methods→Improved boosting algorithms using confidence-rated predictionsLegacy edge — source detail unavailable
• Boosting the margin: a new explanation for the effectiveness of voting methods→Boosting a Weak Learning Algorithm by MajorityLegacy edge — source detail unavailable
• Boosting the margin: a new explanation for the effectiveness of voting methods→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• Boosting the margin: a new explanation for the effectiveness of voting methods→The Strength of Weak LearnabilityLegacy edge — source detail unavailable
• Boosting the margin: a new explanation for the effectiveness of voting methods→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• Boosting the margin: a new explanation for the effectiveness of voting methods→Bagging PredictorsLegacy edge — source detail unavailable
• A study of the behavior of several methods for balancing machine learning training data→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• A study of the behavior of several methods for balancing machine learning training data→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• Improved boosting algorithms using confidence-rated predictions→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• Improved boosting algorithms using confidence-rated predictions→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• Improved boosting algorithms using confidence-rated predictions→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• Extremely randomized trees→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• Extremely randomized trees→Neural Networks and the Bias/Variance DilemmaLegacy edge — source detail unavailable
• Extremely randomized trees→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• Extremely randomized trees→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• Extremely randomized trees→Stacked generalizationLegacy edge — source detail unavailable
• Extremely randomized trees→Random ForestsLegacy edge — source detail unavailable
• Extremely randomized trees→Bagging PredictorsLegacy edge — source detail unavailable
• Machine learning: a review of classification and combining techniques→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• Machine learning: a review of classification and combining techniques→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• Machine learning: a review of classification and combining techniques→Popular Ensemble Methods: An Empirical StudyLegacy edge — source detail unavailable
• Machine learning: a review of classification and combining techniques→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• Machine learning: a review of classification and combining techniques→On the Optimality of the Simple Bayesian Classifier under Zero-One LossLegacy edge — source detail unavailable
• Machine learning: a review of classification and combining techniques→Approximate Statistical Tests for Comparing Supervised Classification Learning AlgorithmsLegacy edge — source detail unavailable
• Machine learning: a review of classification and combining techniques→Bagging PredictorsLegacy edge — source detail unavailable
• Ensembling neural networks: Many could be better than all→Boosting a Weak Learning Algorithm by MajorityLegacy edge — source detail unavailable
• Ensembling neural networks: Many could be better than all→Neural Networks and the Bias/Variance DilemmaLegacy edge — source detail unavailable
• Ensembling neural networks: Many could be better than all→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• Ensembling neural networks: Many could be better than all→The Strength of Weak LearnabilityLegacy edge — source detail unavailable
• Ensembling neural networks: Many could be better than all→Popular Ensemble Methods: An Empirical StudyLegacy edge — source detail unavailable
• Ensembling neural networks: Many could be better than all→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• Ensembling neural networks: Many could be better than all→Stacked generalizationLegacy edge — source detail unavailable
• Ensembling neural networks: Many could be better than all→Bagging PredictorsLegacy edge — source detail unavailable
• Popular Ensemble Methods: An Empirical Study→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• Popular Ensemble Methods: An Empirical Study→Neural Networks and the Bias/Variance DilemmaLegacy edge — source detail unavailable
• Popular Ensemble Methods: An Empirical Study→The Strength of Weak LearnabilityLegacy edge — source detail unavailable
• Popular Ensemble Methods: An Empirical Study→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• Popular Ensemble Methods: An Empirical Study→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• Popular Ensemble Methods: An Empirical Study→Stacked generalizationLegacy edge — source detail unavailable
• Popular Ensemble Methods: An Empirical Study→Bagging PredictorsLegacy edge — source detail unavailable
• Popular Ensemble Methods: An Empirical Study→An Introduction to the BootstrapLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→The foundations of cost-sensitive learningLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→A study of the behavior of several methods for balancing machine learning training dataLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→Improved boosting algorithms using confidence-rated predictionsLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→The Boosting Approach to Machine Learning: An OverviewLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→Random ForestsLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→Bagging PredictorsLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→Improved Boosting Algorithms Using Confidence-rated PredictionsLegacy edge — source detail unavailable
• Exploratory Undersampling for Class-Imbalance Learning→The foundations of cost-sensitive learningLegacy edge — source detail unavailable
• Exploratory Undersampling for Class-Imbalance Learning→A study of the behavior of several methods for balancing machine learning training dataLegacy edge — source detail unavailable
• Exploratory Undersampling for Class-Imbalance Learning→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• Exploratory Undersampling for Class-Imbalance Learning→Stacked generalizationLegacy edge — source detail unavailable
• Exploratory Undersampling for Class-Imbalance Learning→Random ForestsLegacy edge — source detail unavailable
• Exploratory Undersampling for Class-Imbalance Learning→Bagging PredictorsLegacy edge — source detail unavailable
• Experiments with a new boosting algorithm→Boosting a Weak Learning Algorithm by MajorityLegacy edge — source detail unavailable
• Experiments with a new boosting algorithm→The Strength of Weak LearnabilityLegacy edge — source detail unavailable
• Experiments with a new boosting algorithm→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• Experiments with a new boosting algorithm→Bagging PredictorsLegacy edge — source detail unavailable
• Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Ac…→Ensemble Methods in Machine LearningLegacy edge — source detail unavailable
• Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Ac…→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Ac…→Bagging PredictorsLegacy edge — source detail unavailable
• On the Optimality of the Simple Bayesian Classifier under Zero-One Loss→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• A Short Introduction to Boosting→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• A Short Introduction to Boosting→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• A Short Introduction to Boosting→Improved boosting algorithms using confidence-rated predictionsLegacy edge — source detail unavailable
• A Short Introduction to Boosting→Boosting a Weak Learning Algorithm by MajorityLegacy edge — source detail unavailable
• A Short Introduction to Boosting→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• A Short Introduction to Boosting→The Strength of Weak LearnabilityLegacy edge — source detail unavailable
• A Short Introduction to Boosting→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• A Short Introduction to Boosting→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→Ensemble Methods in Machine LearningLegacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→Improved boosting algorithms using confidence-rated predictionsLegacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Ac…Legacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→The Boosting Approach to Machine Learning: An OverviewLegacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→Random ForestsLegacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→Bagging PredictorsLegacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→Improved Boosting Algorithms Using Confidence-rated PredictionsLegacy edge — source detail unavailable
• A few useful things to know about machine learning→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• A few useful things to know about machine learning→On the Optimality of the Simple Bayesian Classifier under Zero-One LossLegacy edge — source detail unavailable
• A few useful things to know about machine learning→Bayesian TheoryLegacy edge — source detail unavailable
• Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms→Bagging PredictorsLegacy edge — source detail unavailable
• Ensemble based systems in decision making→Ensemble Methods in Machine LearningLegacy edge — source detail unavailable
• Ensemble based systems in decision making→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• Ensemble based systems in decision making→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• Ensemble based systems in decision making→The Strength of Weak LearnabilityLegacy edge — source detail unavailable
• Ensemble based systems in decision making→Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Ac…Legacy edge — source detail unavailable
• Ensemble based systems in decision making→Stacked generalizationLegacy edge — source detail unavailable
• Ensemble based systems in decision making→Random ForestsLegacy edge — source detail unavailable
• Ensemble based systems in decision making→Bagging PredictorsLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→Improved boosting algorithms using confidence-rated predictionsLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→Boosting a Weak Learning Algorithm by MajorityLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→The Strength of Weak LearnabilityLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→Improved Boosting Algorithms Using Confidence-rated PredictionsLegacy edge — source detail unavailable
• Ensemble learning: A survey→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• Ensemble learning: A survey→Improved boosting algorithms using confidence-rated predictionsLegacy edge — source detail unavailable
• Ensemble learning: A survey→Extremely randomized treesLegacy edge — source detail unavailable
• Ensemble learning: A survey→Ensembling neural networks: Many could be better than allLegacy edge — source detail unavailable
• Ensemble learning: A survey→Popular Ensemble Methods: An Empirical StudyLegacy edge — source detail unavailable
• Ensemble learning: A survey→Rotation Forest: A New Classifier Ensemble MethodLegacy edge — source detail unavailable
• Ensemble learning: A survey→Ensemble based systems in decision makingLegacy edge — source detail unavailable
• Ensemble learning: A survey→Stacked generalizationLegacy edge — source detail unavailable
• Ensemble learning: A survey→Random ForestsLegacy edge — source detail unavailable
• Random Forests→An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees:…Legacy edge — source detail unavailable
• Random Forests→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• Random Forests→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• Random Forests→Bagging PredictorsLegacy edge — source detail unavailable
• Bagging Predictors→An Introduction to the BootstrapLegacy edge — source detail unavailable
• Improved Boosting Algorithms Using Confidence-rated Predictions→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• Improved Boosting Algorithms Using Confidence-rated Predictions→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• Improved Boosting Algorithms Using Confidence-rated Predictions→Experiments with a new boosting algorithmLegacy edge — source detail unavailable