[Mne_analysis] Classification of ERPs for several subjects

Alexandre Gramfort alexandre.gramfort at telecom-paristech.fr
Thu Nov 19 12:11:01 EST 2015
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hi,

did you follow this example:

http://martinos.org/mne/dev/auto_examples/decoding/plot_decoding_csp_space.html#sphx-glr-auto-examples-decoding-plot-decoding-csp-space-py

?

does it work for you?

Alex



On Thu, Nov 19, 2015 at 4:50 PM, Forooz Shahbazi
<forooz.shahbazi at gmail.com> wrote:
> Hi All,
> I am new to MNE and need your help to classify my ERPs in two different
> conditions for 12 subjects. I would like to combine LDA and CSP for this
> reason in the way that I use the ERPs of let's say 11 subjects and train my
> classifier based on that and to test it on the rest of subjects.
> My problem is in this line of my code:
>
> scores = cross_val_score(clf, evoked_data_array, labels, cv=cv, n_jobs=1)
>
> here, my evoked_data_array is an array of [2* number of subjects(24)*number
> of channels (64)*number of samples of the ERP]. I get this error:
> Found arrays with inconsistent numbers of samples: [24 64]
>
> I guess that's because I am using a 3D array instead of 2D, right? Do you
> have any suggestions how I can solve the issue?
>
> Thank you very much in advance,
> Forooz Shahbazi
>
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