首页|Liaoning Normal University Reports Findings in Support Vector Machines (Assessin g the effectiveness of spatial PCA on SVM-based decoding of EEG data)
Liaoning Normal University Reports Findings in Support Vector Machines (Assessin g the effectiveness of spatial PCA on SVM-based decoding of EEG data)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning - Sup port Vector Machines is the subject of a report. According to news reporting out of Liaoning, People’s Republic of China, by NewsRx editors, research stated, “P rincipal component analysis (PCA) has been widely employed for dimensionality re duction prior to multivariate pattern classification (decoding) in EEG research. The goal of the present study was to provide an evaluation of the effectiveness of PCA on decoding accuracy (using support vector machines) across a broad rang e of experimental paradigms.”
LiaoningPeople’s Republic of ChinaAsiaMachine LearningSupport Vector Machines
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