[pymvpa] What is the value of using errorfx when using Cross validation?
gal.star3051 at gmail.com
Wed Feb 25 15:55:00 UTC 2015
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(),
> 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  for l in fds.sa.chunks])
int_test = numpy.array([l in  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
> 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
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