Hi, Just wondering if anyone had any advice on this… I'm pretty hopelessly stuck and would love to be able to do this RFE-based analysis.
Best, Mike On Fri, Sep 16, 2011 at 6:30 PM, Mike E. Klein <[email protected]>wrote: > Hi all, > > I'm trying to get a very "basic" script working that implements RFE. I'm > not a coder, but I've read the tutorial and am trying to follow others' > scripts as best as possible. Generally, I hope to do small modifications of > standard scripts (changing my 4d bold data, my mask, attributes.txt file, > and label names). > > I tried using the code at http://www.pymvpa.org/featsel.html, but got the > errors mentioned here ( > http://lists.alioth.debian.org/pipermail/pkg-exppsy-pymvpa/2011q2/001747.html), > as I'm running v0.6. (I must also mention that the 0.4, 0.6 (with multiple > RCs), and coming 2.0 naming has been fairly difficult to navigate.) > > Anyway, I followed that thread's advice and changed the method from > camelCase naming to incorporate underscores: that line of code now reads > "sensitivity_analyzer=rfesvm_split.get_sensitivity_analyzer(" > > Python is now reporting a long TypeError which I've pasted below. I've also > attached my script. I've gotten simpler scripts (that incorporate no feature > selection) to work, so the problem should not be with my nifti or attribute > files. > > Thanks again for any and all help: I only have the manual, google, and this > listserv to rely upon when problems arise! > > Best, > Mike > > > In [24]: FtSelClf = FeatureSelectionClassifier( > ....: # use a linear SVM classifier: > ....: clf = LinearCSVMC(), > ....: # on features selected via RFE > ....: feature_selection = RFE( > ....: # based on sensitivity of a clf which does splitting > internally > ....: > sensitivity_analyzer=rfesvm_split.get_sensitivity_analyzer( > ....: transformer=Absolute,combiner=lambda x: > N.sum(x,axis=0)), > ....: transfer_error=ConfusionBasedError( > ....: rfesvm_split, > ....: confusion_state="confusion"), > ....: # and whose internal error we use > ....: feature_selector=FractionTailSelector( > ....: 0.3, mode='discard', tail='lower'), > ....: # remove 20% of features at each step > ....: #enable_states=['feature_ids'], > ....: # update sensitivity at each step > ....: update_sensitivity=True), > ....: enable_states=['feature_ids'], > ....: descr='LinSVM+RFE(splits_avg)') > --------------------------------------------------------------------------- > TypeError Traceback (most recent call last) > /Users/mike/Documents/fMRI_analysis/PyMVPA-analysis/subjects/0-pemberton/<ipython-input-24-85837272a049> > in <module>() > 6 # based on sensitivity of a clf which does splitting > internally > > 7 sensitivity_analyzer=rfesvm_split.get_sensitivity_analyzer( > ----> 8 transformer=Absolute,combiner=lambda x: > N.sum(x,axis=0)), > 9 transfer_error=ConfusionBasedError( > 10 rfesvm_split, > > /Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/mvpa/misc/args.pyc > in do_group_kwargs(self, *args_, **kwargs_) > 71 if passthrough: kwargs__[k] = skwargs > 72 if assign: setattr(self, '_%s' % k, skwargs) > ---> 73 return method(self, *args_, **kwargs__) > 74 do_group_kwargs.func_name = method.func_name > 75 return do_group_kwargs > > /Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/mvpa/clfs/meta.pyc > in get_sensitivity_analyzer(self, slave_kwargs, **kwargs) > 1270 self, sa_attr='splits', > 1271 > analyzer=self.__clf.get_sensitivity_analyzer(**slave_kwargs), > -> 1272 **kwargs) > 1273 > 1274 partitioner = property(fget=lambda x:x.__partitioner, > > /Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/mvpa/misc/args.pyc > in do_group_kwargs(self, *args_, **kwargs_) > 71 if passthrough: kwargs__[k] = skwargs > 72 if assign: setattr(self, '_%s' % k, skwargs) > ---> 73 return method(self, *args_, **kwargs__) > 74 do_group_kwargs.func_name = method.func_name > 75 return do_group_kwargs > > /Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/mvpa/measures/base.pyc > in __init__(self, clf, analyzer, combined_analyzer, sa_attr, slave_kwargs, > **kwargs) > 962 Arguments to pass to created analyzer if analyzer is None > 963 """ > --> 964 Sensitivity.__init__(self, clf, **kwargs) > 965 if combined_analyzer is None: > 966 # sanitarize kwargs > > > /Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/mvpa/measures/base.pyc > in __init__(self, clf, force_train, **kwargs) > 756 # by default auto train > > 757 kwargs['auto_train'] = kwargs.get('auto_train', True) > --> 758 FeaturewiseMeasure.__init__(self, force_train=force_train, > **kwargs) > 759 > 760 _LEGAL_CLFS = self._LEGAL_CLFS > > /Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/mvpa/measures/base.pyc > in __init__(self, **kwargs) > 615 > 616 def __init__(self, **kwargs): > --> 617 Measure.__init__(self, **kwargs) > 618 > 619 > > /Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/mvpa/measures/base.pyc > in __init__(self, null_dist, **kwargs) > 85 certain value of the computed measure. > 86 """ > ---> 87 Learner.__init__(self, **kwargs) > 88 > 89 null_dist_ = auto_null_dist(null_dist) > > /Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/mvpa/base/learner.pyc > in __init__(self, auto_train, force_train, **kwargs) > 76 All arguments are passed to the baseclass. > 77 """ > ---> 78 Node.__init__(self, **kwargs) > 79 self.__is_trained = False > 80 self.__auto_train = auto_train > > /Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/mvpa/base/node.pyc > in __init__(self, space, postproc, **kwargs) > 52 result dataset. If None, nothing is done. > 53 """ > ---> 54 ClassWithCollections.__init__(self, **kwargs) > 55 self.set_space(space) > 56 self.set_postproc(postproc) > > /Library/Frameworks/EPD64.framework/Versions/7.1/lib/python2.7/site-packages/mvpa/base/state.pyc > in __init__(self, descr, **kwargs) > 855 "Unexpected keyword argument %s=%s for > %s." \ > 856 % (arg, argument, self) \ > --> 857 + " Valid parameters are %s" % > known_params > 858 > 859 ## Initialize other base classes > > > TypeError: Unexpected keyword argument transformer=<function Absolute at > 0x1098665f0> for <BoostedClassifierSensitivityAnalyzer>. Valid parameters > are ['base_sensitivities', 'raw_results', 'calling_time', 'training_time', > 'null_t', 'null_prob'] >
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