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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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Related topics

Related topics

13 relations
AlgorithmAnomaly detectionBootstrap aggregatingDecision tree learning

Papers overview

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2019
2019
A Random Subspace Technique That Is Resistant to a Limited Number of Features Corrupted by an Adversary
In this paper, we consider batch supervised learning where an adversary is allowed to corrupt instances with arbitrarily large… 
2017
2017
Linear dimensionality reduction in linear time: Johnson-Lindenstrauss-type guarantees for random subspace
We consider the problem of efficient randomized dimensionality reduction with norm-preservation guarantees. Specifically we prove… 
2015
2015
Optimization of Random Subspace Ensemble for Bankruptcy Prediction
Ensemble classification is to utilize multiple classifiers instead of using a single classifier. Recently ensemble classifiers… 
2014
2014
Fault Detection in Industrial Plant Using κ-Nearest Neighbors with Random Subspace Method
Resumo—In this paper we propose a ensemble approach using κ-nearest neighbors (κ-NN) combined with random subspace method (RSM… 
2014
2014
Combining Diverse Classifiers by Learning Weights Robust to the presence of Class Label Noise
In this paper, we introduced a classifier ensemble approach to combine heterogeneous classifiers together in the presence of… 
2013
2013
Combining one-class support vector machines for microarray classification
The advance of high-throughput techniques, such as gene microarrays and protein chips have a major impact on contemporary biology… 
2010
2010
Random Subspace Method for One-Class Classifiers
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
Semi-random subspace sampling for classification
In this paper, we introduce a novel semi-random subspace sampling for classification (for short, denoted by FS_RS). In this… 
2007
2007
Applying Data Classification Techniques for Churn Prediction in Retailing
Acquiring new customers and retaining loyal customers have been two important tasks for retailers. One critical issue to retain… 
2005
2005
Multiple Classifier Systems, 6th International Workshop, MCS 2005, Seaside, CA, USA, June 13-15, 2005, Proceedings
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