Dear all, I'm struggling with sensitivity analysis. As non-expert MVP analyzer I have some question with respect to this topic:
1) In PyMVPA we have a sensitivity analyzer for each classifier which gives us the importance of dataset features, in the form of a vector of #feature values. These values indicates if a feature is enrolled in the classification task, but not if a feature is more sensitive to a class rather than others. Is there a procedure to understand this or I'm misunderstanding sensitivity analysis? 2) Do you know some papers/lectures/book chapter/ books where can I learn how to understand classifier feature importance? not only in neuroimaging analysis but in general. Thank you! Thank you for your attention RG
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