[pymvpa] Consistently bad accuracy?

Raúl Hernández raul at lafuentelab.org
Mon Nov 26 13:05:40 GMT 2018


I also consider that option, but when I try the very same thing with a
different, region (not related to the task). I get accuracies of 50%. So
that makes me think that it is affected by the task, but I don't know what
to think of it.

Regards

On Mon, Nov 26, 2018 at 1:34 PM Kaustubh Patil <kaustubh.patil at gmail.com>
wrote:

> I suspect that there might be something wrong in the code/how the data is
> handled.
>
> If you 30% accuracy then that would mean that you will get 70% if you use
> a simple rule to predict the "other class" after your classifier. This is a
> sign that something is not right in data handling/evaluation.
>
> Best
>
> On Mon, Nov 26, 2018 at 1:27 PM Raúl Hernández <raul at lafuentelab.org>
> wrote:
>
>> No, it is balanced. It has the same number of observations for each class.
>>
>> On Mon, Nov 26, 2018 at 12:52 PM Kaustubh Patil <kaustubh.patil at gmail.com>
>> wrote:
>>
>>> Just for clarification.
>>>
>>> Is that data imbalanced, i.e. many more observations from one class?
>>>
>>> Best,
>>> Kaustubh
>>>
>>> On Mon, Nov 26, 2018 at 12:50 PM Raúl Hernández <raul at lafuentelab.org>
>>> wrote:
>>>
>>>> Dear PyMVPA community,
>>>>
>>>> I'm doing classification in ROI's, I'm performing a simple 2 way
>>>> classification using LSVM, and a leave-one-run-out cross-validation on 4
>>>> acquisitions. On some ROI's, I get a good accuracy for the number of
>>>> participants (60%), but in others I get consistently bad accuracy (30%). To
>>>> test whether the performance is above chance, I use a one sample t test (I
>>>> know that it is not the best test for this type of data, I just use it as
>>>> quick overview). When I test the bad accuracies, those are also significant.
>>>>
>>>> What does it mean a consistently bad accuracy?
>>>>
>>>> Regards,
>>>>
>>>> Raul
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