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Ensemble learning

Known as: Ensemble Algorithms, Ensemble Methods, Ensemble 
In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained… Expand
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Papers overview

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Review
2019
Review
2019
Abstract Ensemble learning is a prolific field in Machine Learning since it is based on the assumption that combining the output… Expand
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Review
2019
Review
2019
Abstract Network Anomaly Detection Systems (NADSs) are gaining a more important role in most network defense systems for… Expand
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Review
2018
Review
2018
Abstract Class-imbalance learning is one of the most challenging problems in machine learning. As a new and important direction… Expand
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Review
2018
Review
2018
  • Omer Sagi, L. Rokach
  • Wiley Interdiscip. Rev. Data Min. Knowl. Discov.
  • 2018
  • Corpus ID: 49291826
 
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Highly Cited
2012
Highly Cited
2012
An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and… Expand
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Highly Cited
2012
Highly Cited
2012
Today, the most accurate steganalysis methods for digital media are built as supervised classifiers on feature vectors extracted… Expand
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Highly Cited
2011
Highly Cited
2011
Both statistical techniques and Artificial Intelligence (AI) techniques have been explored for credit scoring, an important… Expand
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Highly Cited
2010
Highly Cited
2010
Online learning algorithms often have to operate in the presence of concept drift (i.e., the concepts to be learned can change… Expand
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Highly Cited
2001
Highly Cited
2001
Ensemble methods have recently garnered a great deal of attention in the machine learning community. Techniques such as Boosting… Expand
  • figure 5
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Highly Cited
2000
Highly Cited
2000
  • N. Oza
  • AAAI/IAAI
  • 2000
  • Corpus ID: 40421517
Ensemble learning methods train combinations of base models, which may be decision trees, neural networks, or others… Expand
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