[Mne_analysis] Optimal algorithms for CSP

[JR KING]

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Hi

On Tue, 8 Jan 2019 at 13:00, A S <eng.emetsasa at gmail.com> wrote:

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>
> Hi all,
> I have eeg dataset for 10 subjects. The subjects do the same tasks. I
> applied the common spatial patterns from mne-python package. I used
> with CSP the following algorithms (logistic regression, svc with
> linear kernel,).
> I wanted to compare the algorithms. I found that, for some subjects
> the Logistic Regression performed better, for other subjects the SVC
> with linear Kernel performed better.
> I have following questions:
> for the same tasks is it normal that the optimal algorithm differs
> from subject to another?
>
linear svm with hinge square loss and logistic regression are likely to
provide very similar solutions. So it's likely that they'll randomly be
better for some subjects over other. Some work by Cichy et al suggest that
SVM may be slightly ore robust, but they havent tried it with CSP


Is it normal that the CSP patterns are totally different from subject
>
to another? Why? Is there a literature for this?
>

Subjects topographies, whether taken from CSP or other types of analyses
can vastly differ between subjects because of anatomical differences.

Kindest regards,
JR


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