On Dec 29, 2013, at 4:46 PM, Arman Eshaghi wrote:
> I'm confused on how to pass selected features from SVM sensitivity analysis
> into another SVM for cross validation and performance measurement. [...] Here
> is my script
>
> # from mvpa2.tutorial_suite import *
> # clf=LinearCSVMC()
> # attr = SampleAttributes(os.path.join('/my/path/', 'attributes.txt'))
> # ds= fmri_dataset(samples='/path/to/samples.nii.gz', targets=attr.targets,
> chunks=attr.chunks )
> # fsel = SensitivityBasedFeatureSelection(clf,
> FixedNElementTailSelector(1000, mode='select', tail='upper'))
The first argument of the feature selection has to be a sensitivity analyzer
(of class FeaturewiseMeasure); it cannot be 'just' a classifier
You could try:
sensana=clf.get_sensitivity_analyzer()
and provide sensana as the first argument to SensitivityBasedFeatureSelection.
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