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… (More)
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Papers overview

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Review
2017
Review
2017
In many applications of information systems learning algorithms have to act in dynamic environments where data are collected in… (More)
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Highly Cited
2014
Highly Cited
2014
Article history: Received 27 August 2012 Received in revised form 1 August 2013 Accepted 5 August 2013 Available online 15 August… (More)
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Highly Cited
2007
Highly Cited
2007
The first € price and the £ and $ price are net prices, subject to local VAT. Prices indicated with * include VAT for books; the… (More)
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Highly Cited
2007
Highly Cited
2007
This paper proposes an ensemble method for multilabel classification. The RAndom k-labELsets (RAKEL) algorithm constructs each… (More)
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Highly Cited
2006
Highly Cited
2006
Multi-objective evolutionary algorithms for the construction of neural ensembles is a relatively new area of research. We… (More)
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Highly Cited
2006
Highly Cited
2006
It is well known that the applicability of independent component analysis (ICA) to high-dimensional pattern recognition tasks… (More)
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Highly Cited
2004
Highly Cited
2004
Ensemble learning strategies, especially boosting and bagging decision trees, have demonstrated impressive capacities to improve… (More)
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Highly Cited
2000
Highly Cited
2000
We study resource-limited online learning, motivated by the problem of conditional-branch outcome prediction in computer… (More)
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Highly Cited
1999
Highly Cited
1999
This paper presents a learning approach, i.e. negative correlation learning, for neural network ensembles. Unlike previous… (More)
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Highly Cited
1996
Highly Cited
1996
We describe a decorrelation network training method for improving the quality of regression learning in \en-semble" neural… (More)
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