DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Eun Woo | ko |
dc.contributor.author | Park, HyunWook | ko |
dc.date.accessioned | 2017-03-28T06:50:32Z | - |
dc.date.available | 2017-03-28T06:50:32Z | - |
dc.date.created | 2017-03-06 | - |
dc.date.created | 2017-03-06 | - |
dc.date.issued | 2017-02 | - |
dc.identifier.citation | NEUROSCIENCE BULLETIN, v.33, no.1, pp.41 - 52 | - |
dc.identifier.issn | 1673-7067 | - |
dc.identifier.uri | http://hdl.handle.net/10203/220868 | - |
dc.description.abstract | The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-classifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classifiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses. | - |
dc.language | English | - |
dc.publisher | SPRINGER | - |
dc.subject | INDEPENDENT COMPONENT ANALYSIS | - |
dc.subject | SUPPORT VECTOR MACHINES | - |
dc.subject | FUNCTIONAL CONNECTIVITY | - |
dc.subject | MULTICLASS CLASSIFICATION | - |
dc.subject | FEATURE-SELECTION | - |
dc.subject | RESTING-STATE | - |
dc.subject | HUMAN BRAIN | - |
dc.subject | MR-IMAGES | - |
dc.subject | CORTEX | - |
dc.title | Pairwise Classifier Ensemble with Adaptive Sub-Classifiers for fMRI Pattern Analysis | - |
dc.type | Article | - |
dc.identifier.wosid | 000393071100004 | - |
dc.identifier.scopusid | 2-s2.0-84994694450 | - |
dc.type.rims | ART | - |
dc.citation.volume | 33 | - |
dc.citation.issue | 1 | - |
dc.citation.beginningpage | 41 | - |
dc.citation.endingpage | 52 | - |
dc.citation.publicationname | NEUROSCIENCE BULLETIN | - |
dc.identifier.doi | 10.1007/s12264-016-0077-y | - |
dc.contributor.localauthor | Park, HyunWook | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Ensemble learning | - |
dc.subject.keywordAuthor | Functional MRI | - |
dc.subject.keywordAuthor | Multi-voxel pattern analysis | - |
dc.subject.keywordAuthor | Pairwise classifier | - |
dc.subject.keywordPlus | INDEPENDENT COMPONENT ANALYSIS | - |
dc.subject.keywordPlus | SUPPORT VECTOR MACHINES | - |
dc.subject.keywordPlus | FUNCTIONAL CONNECTIVITY | - |
dc.subject.keywordPlus | MULTICLASS CLASSIFICATION | - |
dc.subject.keywordPlus | FEATURE-SELECTION | - |
dc.subject.keywordPlus | RESTING-STATE | - |
dc.subject.keywordPlus | HUMAN BRAIN | - |
dc.subject.keywordPlus | MR-IMAGES | - |
dc.subject.keywordPlus | CORTEX | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.