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Keyword

ensemble accuracy

Description: The predictive correctness of a combined set of machine-learning models, commonly evaluated in ensemble learning.
OpenAlex ID: keywords/ensemble-accuracy
Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy
2003 · Ludmila I. Kuncheva, Christopher J. Whitaker · Machine Learning · 2,328
Actively Searching for an Effective Neural Network Ensemble
1996 · David W Opitz, Jude W Shavlik · Connection Science · 332
Diversity in search strategies for ensemble feature selection
2004 · Alexey Tsymbal, Mykola Pechenizkiy, et al. · Information Fusion · 321
Relationships between combination methods and measures of diversity in combining classifiers
2002 · Catherine A. Shipp, Ludmila I. Kuncheva · Information Fusion · 270
Ensemble diversity measures and their application to thinning
2004 · Robert E. Banfield, Lawrence O. Hall, et al. · Information Fusion · 221
Weighted cluster ensembles
2009 · Carlotta Domeniconi, Muna Al-Razgan · ACM Transactions on Knowledge Discovery from Data · 203
Is independence good for combining classifiers?
2002 · L.I. Kuncheva, C.J. Whitaker, et al. · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · 195
That Elusive Diversity in Classifier Ensembles
2003 · Ludmila I. Kuncheva · Lecture notes in computer science · 135
“Good” and “Bad” Diversity in Majority Vote Ensembles
2010 · Gavin Brown, Ludmila I. Kuncheva · Lecture notes in computer science · 127
Comparison of Classifier Fusion Methods for Classification in Pattern Recognition Tasks
2006 · Francisco Moreno-Seco, José M. Iñesta, et al. · Lecture notes in computer science · 121
Investigating the influence of the choice of the ensemble members in accuracy and diversity of selection-based and fusion-based methods for ensembles
2006 · Anne M.P. Canuto, Marjory C.C. Abreu, et al. · Pattern Recognition Letters · 101
The impact of diversity on the accuracy of evidential classifier ensembles
2012 · Yaxin Bi · International Journal of Approximate Reasoning · 99
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Full structural ensembles of intrinsically disordered proteins from unbiased molecular dynamics simulations
2021 · Utsab R. Shrestha, Jeremy C. Smith, et al. · Communications Biology · 97
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CIFAR-10: KNN-Based Ensemble of Classifiers
2016 · Yehya Abouelnaga, Ola S. Ali, et al. · International Conference on Computational Science and Computational Intelligence (CSCI) · 96
Effect of Time Delay on Ensemble Accuracy
2004 · Chris Chafe, Michael Gurevich, et al. · 87
A New Ensemble Diversity Measure Applied to Thinning Ensembles
2003 · Robert E. Banfield, Lawrence O. Hall, et al. · Lecture notes in computer science · 86
Considering diversity and accuracy simultaneously for ensemble pruning
2017 · Qun Dai, Rui Ye, et al. · Applied Soft Computing · 81
On diversity and accuracy of homogeneous and heterogeneous ensembles
2007 · Shun Bian, Wenjia Wang · International Journal of Hybrid Intelligent Systems · 81
DIVACE: Diverse and Accurate Ensemble Learning Algorithm
2004 · Arjun Chandra, Xin Yao · Lecture notes in computer science · 81
Optimizing the number of trees in a decision forest to discover a subforest with high ensemble accuracy using a genetic algorithm
2016 · Md Nasim Adnan, Md Zahidul Islam · Knowledge-Based Systems · 78
A Bound on Kappa-Error Diagrams for Analysis of Classifier Ensembles
2011 · Ludmila I. Kuncheva · IEEE Transactions on Knowledge and Data Engineering · 76
Deep Neural Network Ensembles Against Deception: Ensemble Diversity, Accuracy and Robustness
2019 · Ling Liu, Wenqi Wei, et al. · IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (MASS) · 73
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A Boosting-like Online Learning Ensemble
2016 · Roberto Souto Maior de Barros, Silas Garrido T. de Carvalho Santos, et al. · 68
Some fundamental issues in ensemble methods
2008 · Wenjia Wang · IEEE International Joint Conference on Neural Networks (IJCNN) · 64
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The use of entropy to measure structural diversity
2008 · L. Masisi, V. Nelwamondo, et al. · IEEE International Conference on Computational Cybernetics (ICCC) · 60
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Works count: 239
Citation count: 7,126
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