Feature importance analysis

Hi all,

I have succesfully run classification analyses with my EEG data using the SlidingEstimator and GeneralizingEstimator methods and a linear classifier. Now I would like to test which channels are the most informative ones for the models. I have checked some of the sklearn functions but I’m not sure if I can apply those directly to the MNE data. Anyone has done something similar and has some ideas on how to proceed?

Thanks!

if you want to do feature importance analysis eg like explained in https://inria.github.io/scikit-learn-mooc/python_scripts/dev_features_importance.html

I fear you’ll need to reimplement yourself the SlidingEstimator or hack the code in mne.

Alex