Classifying cognitive states of brain activity via one-class neural networks with feature selection by genetic algorithms

International Journal of Machine Learning and Cybernetics

Volumn 2, Issue 3, 2011, Pages 125-134

  Boehm, Omer ^a   Hardoon, David R ^b,c   Manevitz, Larry M ^a  

^a UNIVERSITY OF HAIFA   (Israel)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

^c NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

fMRI; fMRI classification; Genetic algorithms; Neural networks; One class classification

Indexed keywords

BRAIN ACTIVITY; COGNITIVE BRAIN FUNCTION; COGNITIVE STATE; FMRI; FMRI-ANALYSIS; FMRI-CLASSIFICATION; HIGH-DIMENSIONAL; MACHINE LEARNING TECHNIQUES; MICROSOFT RESEARCHES; ONE CLASS-SVM; ONE-CLASS CLASSIFICATION; PERFORMANCE LEVEL; WRAPPER APPROACH;

BRAIN; FEATURE EXTRACTION; GENETIC ALGORITHMS; LEARNING ALGORITHMS; LEARNING SYSTEMS;

NEURAL NETWORKS;

EID: 80051989247     PISSN: 18688071     EISSN: 1868808X     Source Type: Journal    
DOI: 10.1007/s13042-011-0030-3     Document Type: Article

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