[pymvpa] What is the value of using errorfx when using Cross validation?

[gal star]

Hi,
So should be a difference betweeen what i'm doing manually and th Cross
Validation class?

I would also like to understand why the SD is so high between folds.

Thanks,
Gal Star

On Wed, Feb 25, 2015 at 5:55 PM, gal star <gal.star3051 at gmail.com> wrote:

>
>
> On Wed, Feb 25, 2015 at 5:43 PM, Nick Oosterhof <
> n.n.oosterhof at googlemail.com> wrote:
>
>>
>> On 25 Feb 2015, at 16:36, gal star <gal.star3051 at gmail.com> wrote:
>>
>> > Here is the minimal running example:
>> >
>> > fds=fmri_dataset(samples='4D_scans.nii.gz')
>> > zscore(fds, param_est=('targets', ['control']))
>> > int = numpy.array([l in ['class A','class B'] for l in fds.sa.targets])
>> > fds = fds[int]
>> >
>> > clf = FeatureSelectionClassifier(LinearCSVMC(),
>> SensitivityBasedFeatureSeletion(OneWayAnova(),
>> FixedNElementTailSelector(1000 ,tail='upper',mode='select')))
>> >
>> > nfold = NFoldPartitioner(attr='chunks')
>> >
>> > < Python Code for selecting only '0' chunk for train and '1' for test>
>>
>> Can you provide this code please?
>>
>
> int_train = numpy.array([l in [0] for l in fds.sa.chunks])
> int_test = numpy.array([l in [1] for l in fds.sa.chunks])
>
> train = fds[int_train]
> test = fds[int_test]
>
>
>> > clf.train(train)
>> > print clf.predict(test.samples)
>>
>> How exactly do you determine the standard deviation among classification
>> accuracies?
>>
>> I am running this script code k times (each time, different part of the
> data input with '1' chunk). In each time i get an accuracy result. then i'm
> averaging those k results and calculate standard diviation.
>
>
>> Also, the topic of your email is about errorfx, but I didn’t see you
>> using that function anywhere. Could you clarify?
>
>
> Yes, i'm performing manual cross validation, but i've seen that
> if i use the CrossValidation class there is an errrofx parameter.
> I'm trying to understand what is it contributes and how can i use it
> manualy.
>
>
>>
>
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>>
>
>
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