Am 22.07.2012 10:33, schrieb Michael Hanke:
Hi,
On Fri, Jul 20, 2012 at 08:35:25AM +0200, [email protected] wrote:
I'm currently working on my master thesis and using the PyMVPA toolbox for
the analysis of my fMRI data. My script for Recursive Feature Elimination
(RFE) is working with a CrossValidation but unfortunately not with a
SplitClassifier. Could you please give me some advice on that?
In my script (see below) I use the RFE example from the documentation. If
I add a CrossValidation I get an error value for each validation step. But
I'm also interested in the sensitivity maps of each step and I couldn't
figure out if that is possible with CrossValidation. Therefore, I tried to
use a SplittClassifier but I always get the same error message in
self.train(ds).
Could someone tell me the difference between SplitClassifier and
CrossValidation? I assumed that the SplitClassifier also does a
cross-validation internally. What do I have to change in my code to make
it work?
Your assumption is correct and your approach sounds appropriate. Could
you please provide some more information on your dataset (``print
ds.summary``) and the actual error message (incl. traceback) that you
are observing? At first glance, and without this additional information
I can't see an obvious problem.
Cheers,
Michael
It's good to know that I wasn't completely wrong. Here is the error
message and the whole output of ds.summary
Best,
Matthias
*Error message:*
Traceback (most recent call last):
File "RFE_Splitt1.py", line 114, in <module>
sens = cv_sensana(dataset)
File "/usr/lib/pymodules/python2.6/mvpa2/base/learner.py", line 229,
in __call__
self.train(ds)
File "/usr/lib/pymodules/python2.6/mvpa2/base/learner.py", line 119,
in train
result = self._train(ds)
File "/usr/lib/pymodules/python2.6/mvpa2/measures/base.py", line 782,
in _train
return clf.train(dataset)
File "/usr/lib/pymodules/python2.6/mvpa2/base/learner.py", line 119,
in train
result = self._train(ds)
File "/usr/lib/pymodules/python2.6/mvpa2/clfs/meta.py", line 1211, in
_train
clf = clf_template.clone()
File "/usr/lib/pymodules/python2.6/mvpa2/clfs/base.py", line 326, in
clone
return deepcopy(self)
File "/usr/lib/python2.6/copy.py", line 189, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "/usr/lib/python2.6/copy.py", line 338, in _reconstruct
state = deepcopy(state, memo)
File "/usr/lib/python2.6/copy.py", line 162, in deepcopy
y = copier(x, memo)
File "/usr/lib/python2.6/copy.py", line 255, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/usr/lib/python2.6/copy.py", line 189, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "/usr/lib/python2.6/copy.py", line 338, in _reconstruct
state = deepcopy(state, memo)
File "/usr/lib/python2.6/copy.py", line 162, in deepcopy
y = copier(x, memo)
File "/usr/lib/python2.6/copy.py", line 255, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/usr/lib/python2.6/copy.py", line 189, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "/usr/lib/python2.6/copy.py", line 338, in _reconstruct
state = deepcopy(state, memo)
File "/usr/lib/python2.6/copy.py", line 162, in deepcopy
y = copier(x, memo)
File "/usr/lib/python2.6/copy.py", line 255, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/usr/lib/python2.6/copy.py", line 189, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "/usr/lib/python2.6/copy.py", line 338, in _reconstruct
state = deepcopy(state, memo)
File "/usr/lib/python2.6/copy.py", line 162, in deepcopy
y = copier(x, memo)
File "/usr/lib/python2.6/copy.py", line 255, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/usr/lib/python2.6/copy.py", line 162, in deepcopy
y = copier(x, memo)
File "/usr/lib/python2.6/copy.py", line 228, in _deepcopy_list
y.append(deepcopy(a, memo))
File "/usr/lib/python2.6/copy.py", line 189, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "/usr/lib/python2.6/copy.py", line 338, in _reconstruct
state = deepcopy(state, memo)
File "/usr/lib/python2.6/copy.py", line 162, in deepcopy
y = copier(x, memo)
File "/usr/lib/python2.6/copy.py", line 255, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/usr/lib/python2.6/copy.py", line 189, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "/usr/lib/python2.6/copy.py", line 323, in _reconstruct
y = callable(*args)
File "/usr/lib/python2.6/copy_reg.py", line 93, in __newobj__
return cls.__new__(cls, *args)
TypeError: object.__new__(numpy.ufunc) is not safe, use
numpy.ufunc.__new__()
*
ds.summary:*
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