[pymvpa] Performance distribution with random labels
raul at lafuentelab.org
Mon Dec 12 17:02:09 UTC 2016
I’m having trouble getting my head around something and I was wondering if
you can give me a hand.
I’m running a classification with 4 possible categories, 10 runs. My data
is balanced and I’m using CSVM and a leave one out cross-validation.
Just for fun, I wanted to create a distribution of the possible performance
if I randomized the labels of the runs, so I was expecting a performance
around 0.25, after 12,000 reps, I got 0.200, I don’t get it, do you have
This is part of the code I used:
clf = LinearCSVMC()
fclf = FeatureSelectionClassifier(clf, fsel)
cvte = CrossValidation(fclf, NFoldPartitioner(), errorfx=lambda p, t:
np.mean(p == t), enable_ca=['stats'])
for k in range(0,rndReps):
cv_results = cvte(fds)
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