Hi all,
I'm a little bit new to the field of machine learning; I have run ICA on a
set of 20 subjects, and want to use a linear SVM to learn to classify
components as neural or non neural. I'm at a little bit of a loss on how to
do that. I'm following this tutorial:
http://nilearn.github.io/data_analysis/resting_state_networks.html
I realize nilearn is still unsupported, however I figure we can use any ICA
tool to extract components (correct me if I'm wrong?). Basically after
having done this we have 20 components, and for each component we can say
(if we wish) that it is either neural or non neural, and do this for all 20
people. How would this be accomplished using scikit-learn? I appologize if
this is a very broad question, and do thank you for your response in
advance!
-Norman
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