On Wed, Feb 25, 2015 at 5:43 PM, Nick Oosterhof < [email protected]> wrote:
> > On 25 Feb 2015, at 16:36, gal star <[email protected]> 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. > _______________________________________________ > Pkg-ExpPsy-PyMVPA mailing list > [email protected] > http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa >
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