Dear fellow pymvpa users, I have been thinking about RFE as it is shown in the examples section and have a couple questions:
For a multiclass problem, if an SVM is the classifier and the SVMWeights are the sensitivity measure, are the weights for all the child SVMs that must be trained get averaged together to produce a new weight to rank features by? Having used RFE on some multiclass datasets, it's clear that classification performance is improving as features are removed but am unsure what the criterion for removal really means in the multi-class scenario. Also, has anyone tried to get sensitivity maps as described in Hanson, Halchenko 2008? Thanks, Matt
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