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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… 
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Papers overview

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2019
2019
In this paper, we consider batch supervised learning where an adversary is allowed to corrupt instances with arbitrarily large… 
2017
2017
We consider the problem of efficient randomized dimensionality reduction with norm-preservation guarantees. Specifically we prove… 
2015
2015
Ensemble classification is to utilize multiple classifiers instead of using a single classifier. Recently ensemble classifiers… 
2014
2014
Resumo—In this paper we propose a ensemble approach using κ-nearest neighbors (κ-NN) combined with random subspace method (RSM… 
2014
2014
In this paper, we introduced a classifier ensemble approach to combine heterogeneous classifiers together in the presence of… 
2013
2013
The advance of high-throughput techniques, such as gene microarrays and protein chips have a major impact on contemporary biology… 
2010
2010
The goal of one-class classi cation is to distinguish the target class from all the other classes using only training data of the… 
2010
2010
In this paper, we introduce a novel semi-random subspace sampling for classification (for short, denoted by FS_RS). In this… 
2007
2007
Acquiring new customers and retaining loyal customers have been two important tasks for retailers. One critical issue to retain…