[pymvpa] kNN and sensitivity map

[Richard Dinga]

You cannot use sensitivity banalysis with KNN because kNN is not using or
producing any feature weights.

On Tue, May 31, 2016 at 5:39 PM, marco tettamanti <mrctttmnt at gmail.com>
wrote:

> Dear all,
> since kNN performs best on a particular dataset, I am trying to obtain a
> sensitivity map based on the code that I have used for other classifiers.
> However, I receive an error message, and I am not able to proceed further.
> I have been struggling with the documentation, but I still cannot find any
> solutions for this problem.
> Can somebody please help?
> Thank you and best wishes,
> Marco
>
>
>
> This is the relevant snippet:
>
> {fds == fmri dataset}
> clf = kNN(k=2, dfx=one_minus_correlation, voting='majority')
> partitioner = HalfPartitioner()
> fraction=1
> fselaov = SensitivityBasedFeatureSelection(OneWayAnova(),
> FractionTailSelector(fraction, mode='select', tail='upper'))
> fclf = FeatureSelectionClassifier(clf, fselaov)
> fselcvte = CrossValidation(fclf, partitioner, errorfx=lambda p, t:
> np.mean(p == t), postproc=mean_sample(), enable_ca=['confusion', 'stats'])
> res_fsel = fselcvte(fds)
> sensana = fclf.get_sensitivity_analyzer(postproc=maxofabs_sample())
>
>
>
>
> This is the error message:
>
> ---------------------------------------------------------------------------
> NotImplementedError                        Traceback (most recent call
> last)
> <ipython-input-32-2e8317c1b278>  in<module>() ----> 1sensana =
> fclf.get_sensitivity_analyzer(postproc=maxofabs_sample())
> 2  #sensana = fclf.get_sensitivity_analyzer(postproc=absolute_features())
> 3  #sensana = fclf.get_sensitivity_analyzer(postproc=mean_sample())
> 4  cv_sensana=  RepeatedMeasure(sensana,  ChainNode((partitioner,
> Splitter('partitions',  attr_values=(1,)))))
> 5  sens=  cv_sensana(fds)
>
> /usr/lib/python2.7/dist-packages/mvpa2/misc/args.pyc
> indo_group_kwargs(self, *args_, **kwargs_) 73 if passthrough:
> kwargs__[k]  =  skwargs
> 74                  if  assign:  setattr(self,  '_%s'  %  k,  skwargs)
> ---> 75return method(self,  *args_,  **kwargs__)
> 76          do_group_kwargs.func_name=  method.func_name
> 77          return  do_group_kwargs
>
> /usr/lib/python2.7/dist-packages/mvpa2/clfs/meta.pyc
> inget_sensitivity_analyzer(self, slave_kwargs, **kwargs) 329 return
> self.__sa_class__( 330 self,
> --> 331analyzer=self.__clf.get_sensitivity_analyzer(**slave_kwargs),
> 332                  **kwargs)
> 333
> /usr/lib/python2.7/dist-packages/mvpa2/clfs/base.pyc
> inget_sensitivity_analyzer(self, **kwargs) 492 """Factory method to return
> an appropriate sensitivity analyzer for 493 the respective classifier."""
> --> 494raise NotImplementedError
> 495  496
> NotImplementedError:
>
>
>
>
> This are the code and OS versions:
>
> Current date:   2016-05-31 17:22
> PyMVPA:
>  Version:       2.5.0
>  Hash:          6a9d4060ad863f99170801854c272b61af51f015
>  Path:          /usr/lib/python2.7/dist-packages/mvpa2/__init__.pyc
>  Version control (GIT):
>  GIT information could not be obtained due
> "/usr/lib/python2.7/dist-packages/mvpa2/.. is not under GIT"
> SYSTEM:
>  OS:            posix Linux 4.3.0-1-amd64 #1 SMP Debian 4.3.3-7
> (2016-01-19)
>  Distribution:  debian/stretch/sid
> EXTERNALS:
>  Present:       atlas_fsl, cPickle, ctypes, good
> scipy.stats.rv_continuous._reduce_func(floc,fscale), good
> scipy.stats.rv_discrete.ppf, griddata, gzip, h5py, hdf5, ipython, joblib,
> liblapack.so, libsvm, libsvm verbosity control, lxml, matplotlib, mdp, mdp
> ge 2.4, mock, nibabel, nipy, nose, numpy, numpy_correct_unique, pprocess,
> pylab, pylab plottable, pywt, pywt wp reconstruct, reportlab, running
> ipython env, scipy, scipy.weave, sg ge 0.6.4, sg ge 0.6.5,
> sg_fixedcachesize, shogun, shogun.mpd, shogun.svmocas, skl, statsmodels
>  Absent:        atlas_pymvpa, cran-energy, datalad, elasticnet, glmnet,
> good scipy.stats.rdist, hcluster, lars, mass, nipy.neurospin, numpydoc,
> openopt, pywt wp reconstruct fixed, rpy2, shogun.krr, shogun.lightsvm,
> shogun.svrlight, weave
>  Versions of critical externals:
>   ctypes      : 1.1.0
>   h5py        : 2.5.0
>   hdf5        : 1.8.13
>   ipython     : 2.3.0
>   joblib      : 0.9.4
>   lxml        : 3.4.4
>   matplotlib  : 1.4.2
>   mdp         : 3.5
>   mock        : 1.3.0
>   nibabel     : 2.0.2
>   nipy        : 0.4.0.dev
>   numpy       : 1.8.2
>   pprocess    : 0.5
>   reportlab   : 3.2.0
>   scipy       : 0.14.1
>   shogun      : 3.2.0
>   shogun:full : 3.2.0_2014-2-17_18:46
>   shogun:rev  : 197120
>   skl         : 0.17.1
>  Matplotlib backend: module://IPython.kernel.zmq.pylab.backend_inline
>
>
> --
> Marco Tettamanti, Ph.D.
> Nuclear Medicine Department & Division of Neuroscience
> San Raffaele Scientific Institute
> Via Olgettina 58
> I-20132 Milano, Italy
> Phone ++39-02-26434888
> Fax ++39-02-26434892
> Email: tettamanti.marco at hsr.it
> Skype: mtettamanti
>
>
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