Output details
11 - Computer Science and Informatics
Bangor University
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Output 0 of 0 in the submission
Article title
Classifier ensembles for fMRI data analysis: an experiment
Type
D - Journal article
Title of journal
Magnetic Resonance Imaging
Article number
-
Volume number
28
Issue number
4
First page of article
583
ISSN of journal
0730725X
Year of publication
2010
URL
-
Number of additional authors
1
Additional information
<24>fMRI data analysis thus far has made little use of the achievements and potential of modern machine learning and pattern recognition. This paper introduces state-of-the-art techniques, specifically classifier ensembles, to fMRI data analysis demonstrating that these techniques can outperform the current favourite (Support Vector Machine classifier - SVM). Ranked 12 among the 25 top downloads in the journal for academic year 2009-2010.
http://top25.sciencedirect.com/subject/physics-and-astronomy/21/journal/magnetic-resonance-imaging/0730725X/archive/29/
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
28
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
