[pymvpa] Problems interpreting GroupClusterThresholding results

[Bill Broderick]

Hi all,

Thanks for the pointers! The algorithm runs find with error between 0 and
2, though I'm running into some issues because I forgot to include the
mapper for my dataset in the permutation dataset and when I combined all
the subject-level actual results into one dataset. So PyMVPA is stuck using
the IdentityMapper, which definitely doesn't work. It would be helpful if
GroupClusterThreshold printed a warning if the datasets it's training or
called on don't have any mappers, since it's unlikely that a user will
actually use this on a dataset without any mappers, right?

Thanks,
Bill

On Mon, Sep 28, 2015 at 10:51 AM, Michael Hanke <michael.hanke at gmail.com>
wrote:

> Hi,
>
> On Mon, Sep 28, 2015 at 4:42 PM, Richard Dinga <dinga92 at gmail.com> wrote:
>
>> > I'm performing searchlight support vector regression, not classification,
>> > so my error goes from 0 to 2 instead of 0 to 1. Can I simply take `2 -
>> > error` (so higher is better) or does the algorithm require the values to
>> > lie between 0 and 1?
>>
>> You can do that, as long as higher is better. Algorithm will just sort them and find nth biggest value.
>>
>> > The docs say the accuracy maps must be the result of
>> > classification, but is there a specific reason regression won't work?
>>
>> I have no idea :) Original paper doesn't mention regression. Will p-values and FDR still make sense?
>>
>> Right now I cannot think of a reason we it wouldn't work -- as long as
> "bigger is better".
>
> The algorithm converts pretty much anything into
> probabilities/frequencies. 1. Value corresponding to a particular
> probability under H0 -> threshold. 2. frequency with which a particular
> blob size has been observered in a group average map under H0.
>
> Should work.
>
> Michael
>
>
>
>
> --
> Michael Hanke
> http://mih.voxindeserto.de
>
>
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