[pymvpa] Customize ANOVA Feature Selection

[Roberto Guidotti]

Thank you for the response,

I'm always lazy to improve problem description (and my english doesn't help
me!!!)

Theoretically for every fold I have to select important features, so I
perform ANOVA, the algorithm ranks my feature, but I want to drop the first
1% and use the 5% (or X%) of the new rank after 1% dropping.  I found on my
analysis that most important feature are, in the 90% of cases, on the brain
edge (probably motion artefacts voxels that still affect the dataset also
after preprocessing).
For this reason I would like to extract ANOVA ranking stack or to find a
method to use voxels from 1.01% to 5.01%!

So I want to perform ANOVA on data, drop the first 1%, select the new
ranking stack (5% of residual voxels)  and train the classifier!

Thank you
RG

On 3 October 2011 18:14, Yaroslav Halchenko <debian at onerussian.com> wrote:

> I might be missing the problem since you seem to have to know the blocks
> you need ;)  so following the example from the clfs warehouse:
>
>    FeatureSelectionClassifier(
>        kNN(),
>        SensitivityBasedFeatureSelection(
>           OneWayAnova(),
>           FractionTailSelector(0.05, mode='select', tail='upper')),
>        descr="kNN on 5%(ANOVA)")
>
> logical change would be to use 0.99 instead of 0.05 to select 99% top
> voxels
> (or in other words to dump 1%)... or just change mode to 'discard' and
> specify
> 0.01 as the fraction
>
> On Mon, 03 Oct 2011, Roberto Guidotti wrote:
>
> >    Hi all,
>
> >    I would like to know if there is a method to extract the feature
> >    ranking from ANOVA feature selection or if there is a method to drop
> >    first 1% of voxel included in the ranking and select other voxel as
> >    usual (with FractionTailSelection()).
>
> >    Thank you
>
> >    Roberto
>
> > _______________________________________________
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> >
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>
>
> --
> =------------------------------------------------------------------=
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> Yaroslav Halchenko                 www.ohloh.net/accounts/yarikoptic
>
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