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Bootstrap aggregating

Known as: Bootstrap aggregation, Bootstrapped Aggregation, Bootstrapping (machine learning) 
Bootstrap aggregating, also called bagging, is a machine learning ensemble meta-algorithm designed to improve the stability and accuracy of machine… Expand
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Papers overview

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Highly Cited
2016
Highly Cited
2016
Abstract Computer-aided sleep staging based on single channel electroencephalogram (EEG) is a prerequisite for a feasible low… Expand
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Highly Cited
2013
Highly Cited
2013
Classification with imbalanced data-sets has become one of the most challenging problems in Data Mining. Being one class much… 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
2010
Highly Cited
2010
Context: In software industry, project managers usually rely on their previous experience to estimate the number men/hours… Expand
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Highly Cited
2004
Highly Cited
2004
Leo Breiman’s Random Forest ensemble learning procedure is applied to the problem of Quantitative Structure-Activity Relationship… Expand
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Highly Cited
2002
Highly Cited
2002
We propose an algorithm for regression tree construction called GUIDE. It is specifically designed to eliminate variable… Expand
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Highly Cited
2002
Highly Cited
2002
We prove new probabilistic upper bounds on generalization error of complex classifiers that are combinations of simple… Expand
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Highly Cited
2001
Highly Cited
2001
This paper presents an active learning method that directly optimizes expected future error. This is in contrast to many other… Expand
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Highly Cited
2000
Highly Cited
2000
We briefly describe our approach for the KDD99 Classification Cup. The solution is essentially a mixture of bagging and boosting… Expand
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Highly Cited
1998
Highly Cited
1998
Combining multiple classi ers is an e ective technique for improving accuracy. There are many general combining algorithms, such… Expand
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