The Boosting Approach to Machine Learning: An Overview

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• The Algorithmic Foundations of Differential Privacy→The Boosting Approach to Machine Learning: An OverviewLegacy edge — source detail unavailable
• Gradient boosting machines, a tutorial→The Boosting Approach to Machine Learning: An OverviewLegacy edge — source detail unavailable
• Model compression→The Boosting Approach to Machine Learning: An OverviewLegacy edge — source detail unavailable
• Rotation Forest: A New Classifier Ensemble Method→The Boosting Approach to Machine Learning: An OverviewLegacy edge — source detail unavailable
• CLASSIFICATION OF IMBALANCED DATA: A REVIEW→The Boosting Approach to Machine Learning: An OverviewLegacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→The Boosting Approach to Machine Learning: An OverviewLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→The Nature of Statistical Learning TheoryLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→Support-Vector NetworksLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→Greedy function approximation: A gradient boosting machine.Legacy 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→A training algorithm for optimal margin classifiersLegacy 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→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→Fast Effective Rule InductionLegacy 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→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→Solving Multiclass Learning Problems via Error-Correcting Output CodesLegacy 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
• 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→On the Uniform Convergence of Relative Frequencies of Events to Their ProbabilitiesLegacy 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→UCI Repository of Machine Learning DatabasesLegacy edge — source detail unavailable
• The Boosting Approach to Machine Learning: An Overview→BoosTexter: A Boosting-based System for Text CategorizationLegacy 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→Learnability and the Vapnik-Chervonenkis dimensionLegacy 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→What Size Net Gives Valid Generalization?Legacy 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:…→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:…→UCI Repository of Machine Learning DatabasesLegacy edge — source detail unavailable
• Fast Effective Rule Induction→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• Solving Multiclass Learning Problems via Error-Correcting Output Codes→The Strength of Weak LearnabilityLegacy edge — source detail unavailable
• Greedy function approximation: A gradient boosting machine.→Improved boosting algorithms using confidence-rated predictionsLegacy edge — source detail unavailable
• Greedy function approximation: A gradient boosting machine.→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• Greedy function approximation: A gradient boosting machine.→The Nature of Statistical Learning TheoryLegacy 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→Solving Multiclass Learning Problems via Error-Correcting Output CodesLegacy 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→A training algorithm for optimal margin classifiersLegacy 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→Support-Vector NetworksLegacy edge — source detail unavailable
• Boosting the margin: a new explanation for the effectiveness of voting methods→The Nature of Statistical Learning TheoryLegacy edge — source detail unavailable
• Boosting the margin: a new explanation for the effectiveness of voting methods→What Size Net Gives Valid Generalization?Legacy 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→On the Uniform Convergence of Relative Frequencies of Events to Their ProbabilitiesLegacy edge — source detail unavailable
• CLASSIFICATION OF IMBALANCED DATA: A REVIEW→Improved boosting algorithms using confidence-rated predictionsLegacy edge — source detail unavailable
• CLASSIFICATION OF IMBALANCED DATA: A REVIEW→Cost-sensitive boosting for classification of imbalanced dataLegacy edge — source detail unavailable
• CLASSIFICATION OF IMBALANCED DATA: A REVIEW→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• CLASSIFICATION OF IMBALANCED DATA: A REVIEW→Improved Boosting Algorithms Using Confidence-rated PredictionsLegacy 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→Solving Multiclass Learning Problems via Error-Correcting Output CodesLegacy 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
• Improved boosting algorithms using confidence-rated predictions→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Improved boosting algorithms using confidence-rated predictions→What Size Net Gives Valid Generalization?Legacy edge — source detail unavailable
• Improved boosting algorithms using confidence-rated predictions→UCI Repository of Machine Learning DatabasesLegacy edge — source detail unavailable
• BoosTexter: A Boosting-based System for Text Categorization→Fast Effective Rule InductionLegacy edge — source detail unavailable
• BoosTexter: A Boosting-based System for Text Categorization→Boosting the margin: a new explanation for the effectiveness of voting methodsLegacy edge — source detail unavailable
• BoosTexter: A Boosting-based System for Text Categorization→Improved boosting algorithms using confidence-rated predictionsLegacy edge — source detail unavailable
• BoosTexter: A Boosting-based System for Text Categorization→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
• A training algorithm for optimal margin classifiers→What Size Net Gives Valid Generalization?Legacy edge — source detail unavailable
• Gradient boosting machines, a tutorial→Greedy function approximation: A gradient boosting machine.Legacy edge — source detail unavailable
• The Strength of Weak Learnability→Learnability and the Vapnik-Chervonenkis dimensionLegacy 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→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→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Cost-sensitive boosting for classification of imbalanced data→Improved Boosting Algorithms Using Confidence-rated PredictionsLegacy edge — source detail unavailable
• Experiments with a new boosting algorithm→Fast Effective Rule InductionLegacy 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
• Support-Vector Networks→A training algorithm for optimal margin classifiersLegacy 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→C4.5: Programs for Machine LearningLegacy 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
• Rotation Forest: A New Classifier Ensemble Method→Improved Boosting Algorithms Using Confidence-rated PredictionsLegacy 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…→Boosting a Weak Learning Algorithm by MajorityLegacy 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…→The Strength of Weak LearnabilityLegacy 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…→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
• Learnability and the Vapnik-Chervonenkis dimension→What Size Net Gives Valid Generalization?Legacy edge — source detail unavailable
• Learnability and the Vapnik-Chervonenkis dimension→On the Uniform Convergence of Relative Frequencies of Events to Their ProbabilitiesLegacy edge — source detail unavailable
• What Size Net Gives Valid Generalization?→Learnability and the Vapnik-Chervonenkis dimensionLegacy edge — source detail unavailable
• Model compression→UCI Repository of machine learning databasesLegacy edge — source detail unavailable
• Improved Boosting Algorithms Using Confidence-rated Predictions→Solving Multiclass Learning Problems via Error-Correcting Output CodesLegacy 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
• Improved Boosting Algorithms Using Confidence-rated Predictions→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Improved Boosting Algorithms Using Confidence-rated Predictions→What Size Net Gives Valid Generalization?Legacy edge — source detail unavailable