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MCS
2010
Springer
13 years 6 months ago
Choosing Parameters for Random Subspace Ensembles for fMRI Classification
Abstract. Functional magnetic resonance imaging (fMRI) is a noninvasive and powerful method for analysis of the operational mechanisms of the brain. fMRI classification poses a sev...
Ludmila I. Kuncheva, Catrin O. Plumpton
TMI
2010
206views more  TMI 2010»
12 years 11 months ago
Random Subspace Ensembles for fMRI Classification
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
Ludmila I. Kuncheva, Juan José Rodrí...
ICPR
2010
IEEE
13 years 8 months ago
On-Line Fmri Data Classification Using Linear and Ensemble Classifiers
The advent of real-time fMRI pattern classification opens many avenues for interactive self-regulation where the brain's response is better modelled by multivariate, rather t...
Catrin Oliver Plumpton, Ludmila I. Kuncheva, David...
MCS
2007
Springer
13 years 10 months ago
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Joseph DePasquale, Robi Polikar
IJCV
2006
206views more  IJCV 2006»
13 years 4 months ago
Random Sampling for Subspace Face Recognition
Subspacefacerecognitionoftensuffersfromtwoproblems:(1)thetrainingsamplesetissmallcompared with the high dimensional feature vector; (2) the performance is sensitive to the subspace...
Xiaogang Wang, Xiaoou Tang