Stacked generalization

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

• Deep learning in neural networks: An overview→Stacked generalizationLegacy edge — source detail unavailable
• A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection→Stacked generalizationLegacy edge — source detail unavailable
• Extremely randomized trees→Stacked generalizationLegacy edge — source detail unavailable
• Wrappers for feature subset selection→Stacked generalizationLegacy edge — source detail unavailable
• On combining classifiers→Stacked generalizationLegacy edge — source detail unavailable
• Learning Deep Architectures for AI→Stacked generalizationLegacy edge — source detail unavailable
• Ensemble learning: A survey→Stacked generalizationLegacy edge — source detail unavailable
• Popular Ensemble Methods: An Empirical Study→Stacked generalizationLegacy edge — source detail unavailable
• Ensemble based systems in decision making→Stacked generalizationLegacy edge — source detail unavailable
• An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→Stacked generalizationLegacy edge — source detail unavailable
• Exploratory Undersampling for Class-Imbalance Learning→Stacked generalizationLegacy edge — source detail unavailable
• Ensemble deep learning: A review→Stacked generalizationLegacy edge — source detail unavailable
• Model compression→Stacked generalizationLegacy edge — source detail unavailable
• Ensembling neural networks: Many could be better than all→Stacked generalizationLegacy edge — source detail unavailable
• Neural Network Ensembles, Cross Validation, and Active Learning→Stacked generalizationLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Stacked generalizationLegacy edge — source detail unavailable
• A Review of Relational Machine Learning for Knowledge Graphs→Stacked generalizationLegacy edge — source detail unavailable
• Neural networks for classification: a survey→Stacked generalizationLegacy edge — source detail unavailable
• Orange: data mining toolbox in python→Stacked generalizationLegacy edge — source detail unavailable
• Building Watson: An Overview of the DeepQA Project→Stacked generalizationLegacy edge — source detail unavailable
• Automated Machine Learning→Stacked generalizationLegacy edge — source detail unavailable
• Mining Multi-label Data→Stacked generalizationLegacy edge — source detail unavailable
• Stacked generalization→Adaptation in Natural and Artificial SystemsLegacy edge — source detail unavailable
• Stacked generalization→Induction of Decision TreesLegacy edge — source detail unavailable
• Stacked generalization→Induction of decision treesLegacy edge — source detail unavailable
• A Review of Relational Machine Learning for Knowledge Graphs→Building Watson: An Overview of the DeepQA ProjectLegacy edge — source detail unavailable
• Wrappers for feature subset selection→A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model SelectionLegacy edge — source detail unavailable
• Wrappers for feature subset selection→Neural Network Ensembles, Cross Validation, and Active LearningLegacy edge — source detail unavailable
• Wrappers for feature subset selection→Induction of Decision TreesLegacy edge — source detail unavailable
• Wrappers for feature subset selection→Induction of decision treesLegacy edge — source detail unavailable
• Extremely randomized trees→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Adaptation in Natural and Artificial SystemsLegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Learning Deep Architectures for AILegacy edge — source detail unavailable
• Deep learning in neural networks: An overview→Deep Learning: Methods and ApplicationsLegacy 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→Neural Network Ensembles, Cross Validation, and Active LearningLegacy 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
• Popular Ensemble Methods: An Empirical Study→Neural Network Ensembles, Cross Validation, and Active LearningLegacy 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
• Exploratory Undersampling for Class-Imbalance Learning→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Neural networks for classification: a survey→Neural Network Ensembles, Cross Validation, and Active LearningLegacy edge — source detail unavailable
• Neural networks for classification: a survey→On combining classifiersLegacy edge — source detail unavailable
• Deep Learning: Methods and Applications→Learning Deep Architectures for AILegacy 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
• On combining classifiers→Neural Network Ensembles, Cross Validation, and Active LearningLegacy 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
• Ensemble based systems in decision making→On combining classifiersLegacy 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→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
• Ensemble learning: A survey→Ensemble based systems in decision makingLegacy edge — source detail unavailable
• Ensemble learning: A survey→Model compressionLegacy edge — source detail unavailable
• Ensemble deep learning: A review→Neural Network Ensembles, Cross Validation, and Active LearningLegacy edge — source detail unavailable
• Ensemble deep learning: A review→Deep Learning: Methods and ApplicationsLegacy edge — source detail unavailable
• Ensemble deep learning: A review→Ensemble learning: A surveyLegacy edge — source detail unavailable
• Automated Machine Learning→A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model SelectionLegacy edge — source detail unavailable
• Mining Multi-label Data→Wrappers for feature subset selectionLegacy edge — source detail unavailable