Adaptive schemes applied to online SVM for BCI data classification
Mohammadreza Asghari Oskoei, John Q. Gan, Huosheng Hu · 2009
This paper evaluates supervised and unsupervised adaptive schemes applied to online support vector machine (SVM) that classifies BCI data. Online SVM processes fresh samples as they come and update existing support vectors without referring to pervious samples. It is shown that the performance of online SVM is similar to that of the standard SVM, and both supervised and unsupervised schemes improve the classification hit rate.