[pymvpa] Use case for recursive feature elimination

Michael Waskom mwaskom at MIT.EDU
Mon Nov 1 21:45:53 UTC 2010


Hmm, on second thought, I can't quite seem to get this to work.  Trying the
example from __test_matthias_question line for line, it throws a TypeError
on classifier initialization.

TypeError: Unexpected keyword argument transformer=<ufunc 'absolute'> for
BoostedClassifierSensitivityAnalyzer: 4 ca:ca{base_sensitivities raw_results
null_t null_prob+}. Valid parameters are ['base_sensitivities',
'raw_results', 'null_t', 'null_prob']

wtf, right?
Current date:   2010-11-01 17:43
PyMVPA:
 Version:       0.5.0.dev
 Path:
 /software/python/nipype0.3/lib/python2.6/site-packages/pymvpa-0.5.0.dev-py2.6-linux-x86_64.egg/mvpa/__init__.pyc
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 GIT information could not be obtained due
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On Mon, Nov 1, 2010 at 2:10 PM, Michael Waskom <mwaskom at mit.edu> wrote:

> Hi Yarik,
>
> Thanks!  The pointer to that test is very helpful indeed.
>
> Best,
> Mike
>
>
> On Mon, Nov 1, 2010 at 2:02 PM, Yaroslav Halchenko <yoh at dartmouth.edu>wrote:
>
>> Hi Mike,
>>
>> sorry that it causes you troble... but RFE is indeed somewhat difficult
>> to figure out...
>>
>> but before anything:
>> have you seen
>> http://dev.pymvpa.org/featsel.html#recursive-feature-elimination
>>
>> also look may be at
>> mvpa/tests/test_rfe.py:    def __test_matthias_question(self):
>> which has one of RFE structures
>>
>> in general classifier with RFE as feature selection should be treated as
>> any other classifier
>>
>> also -- do you really think that RFE is necessary in your case? may be
>> some simpler feature selection or SMLR would do?
>>
>> P.S. it would be of greater benefit to everyone if we continue this
>> communication on the mailing list, if you don't mind of cause
>>
>> On Mon, 01 Nov 2010, Michael Waskom wrote:
>>
>> >    Hey Yarik,
>>
>> >    I'm trying to figure out how to use the RFE class in pymvpa 0.5dev.
>> >    Sadly, there doesn't seem to be much in the (otherwise
>> >    super-helpful) documentation about it.  I get all of the parameters,
>> >    but I'm not quite sure how it might fit into a typical analysis, and
>> >    I'm very interested in trying out some recursive feature selection.
>>  Do
>> >    you have a simple use case you could put up as a gist (or elsewhere)
>> so
>> >    I can get the basic idea?  Nothing too didactic is required.
>>
>> >    Thanks!
>>
>> >    Mike
>>
>> --
>> Yaroslav O. Halchenko
>> Postdoctoral Fellow,   Department of Psychological and Brain Sciences
>> Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
>> Phone: +1 (603) 646-9834                       Fax: +1 (603) 646-1419
>> WWW:   http://www.linkedin.com/in/yarik
>>
>
>
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