[Mne_analysis] Cluster-based Permutation T-test for Decoders
Maryam.Zolfaghar at colorado.edu
Thu Oct 10 14:22:59 EDT 2019
External Email - Use Caution
Thanks for the response.
Does AUC take care of the multiple comparison issues? How I will be sure
that the accuracy is significant (above chance)?
On Thu, Oct 10, 2019 at 4:04 AM JR KING <jeanremi.king at gmail.com> wrote:
> You can use a one-versus-all classifier and compute the average AUC
> across categories
> On Thu, 10 Oct 2019 at 05:24, Maryam Zolfaghar <
> Maryam.Zolfaghar at colorado.edu> wrote:
>> External Email - Use Caution
>> Hi all,
>> I am trying to
>> - use decoders to decode whether ERP or time-frequency signals have
>> any meaninful information of four classes (location of the target on the
>> screen) in my experiment *over time *(according to this example
>> - and then test whether the output of the decoder is significantly
>> above the chance (in my case: 1/4=0.25) using a permutation t-test with
>> cluster-based correction.
>> My question is:
>> - In the example
>> there are only two classes, so AUC was used. However, what if there are
>> more than two classes? How I can analyze the significance of the decoder's
>> output with the cluster-based correction?
>> Mne_analysis mailing list
>> Mne_analysis at nmr.mgh.harvard.edu
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