Hi,
I think that what you are trying to do is exactly what FSL FIX does. See
the references in the documentation page:
http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FIX
Alexandre.
On Wed, Dec 3, 2014 at 6:15 PM, Norman Benbrahim <normanbenbra...@gmail.com>
wrote:
> 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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