While performing the signal classification process, say it for example in EEG signal classification for detection for any wave parameter, which classifier gives most efficient and fast performance result?
I agree with the answer given by Isaac, the features play a prominent role in deciding the accuracy of the classifier. the frequency domain features prove to increase the accuracy of classification to a greater extent.
also, complex neural structures like Radial Basis functions are better suitable for classification problems.
In the case of epileptic seizure detection, either Support Vector Machines (SVM Classifiers) will be giving optimal output or Naive Bayes Classifier?
For two labels, i m using an additional optimization algorithm called ICA - Independent Component Analysis Functions, which i m getting fastest result..
Hi,
maybe this paper can help:
Support vector machines to detect physiological patterns for EEG and EMG-based human–computer interaction: a review
http://iopscience.iop.org/article/10.1088/1741-2552/14/1/011001/meta;jsessionid=3BDF7DFCE08E1F71A7A221DFCB3D230C.ip-10-40-1-105
Article Support vector machines to detect physiological patterns for...
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