Random subspace method

Known as: Attribute bagging 
In machine learning. the random subspace method, also called attribute bagging or feature bagging, is an ensemble learning method that attempts to… (More)
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Topic mentions per year

Topic mentions per year

1998-2016
0102019982016

Papers overview

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2012
2012
Over fitting is a common problem for gait recognition algorithms when gait sequences in gallery for training are acquired under a… (More)
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2010
2010
In text categorization (TC), which is a supervised technique, a feature vector of terms or phrases is usually used to represent… (More)
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2010
2010
With growing attention to ensemble learning, in recent years various ensemble methods for face recognition have been proposed… (More)
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2009
2009
2. State Key Lab. for Novel Software Technology, Nanjing University, P.R. China Abstract: The small sample size (SSS) and the… (More)
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2008
2008
In this paper we propose a boosting approach to random subspace method (RSM) to achieve an improved performance and avoid some of… (More)
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2008
2008
Semi-supervised learning has received much attention recently. Co-training is a kind of semi-supervised learning method which… (More)
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Highly Cited
2006
Highly Cited
2006
In a growing number of domains the data collected has a large number of features. This poses a challenge to classical pattern… (More)
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Highly Cited
2006
Highly Cited
2006
Relevance feedback schemes based on support vector machines (SVM) have been widely used in content-based image retrieval (CBIR… (More)
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Highly Cited
2002
Highly Cited
2002
Recently bagging, boosting and the random subspace method have become popular combining techniques for improving weak classifiers… (More)
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Highly Cited
1998
Highly Cited
1998
  • Tin Kam Ho
  • IEEE Trans. Pattern Anal. Mach. Intell.
  • 1998
Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma… (More)
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