[pymvpa] NSplitter?

[Per B. Sederberg]

Howdy Y:

I think coarsen chunks will work, but i'm confused by all the methods
of doing what I want, which I think is simpler than what you described
in your email.

HalfSplitter makes two splits (right down the middle).  you could
imagine ThirdSplitter, which splits your data into thirds, etc...
this is all that coarsen chunks is doing along with nfoldsplitter, but
why force two steps?  if I only wanted coarsenchunks(2), I could just
call HalfSplitter, which already exists?

perhaps I shouldn't send tired emails from my phone in bed.  i'll try
and clairify tomorrow...

latros,
p

On 3/27/09, Yaroslav Halchenko <debian at onerussian.com> wrote:
>
>> I was helping a colleague perform a multivariate analysis of EEG data
>> today and we ran into a missing splitter issue.  Given that it's EEG
>> there's no real need for chunks, like in fMRI runs, and we didn't want
>> to run an NFoldSplitter-based cross validation (CV) because it would,
>> quite possibly, take forever.  Instead, we simply wanted to run a CV
>> by splitting the data into 10 chunks (though we could try different
>> numbers of splits).
>
> just look at our Frontiers paper code ;)
>
> I guess you just want to use
>
> coarsenChunks(10)  with NFoldSplitter ;)
>
> or may be look at the docstring of Splitter at such parameters as
> nperlabel, count and strategy. Not sure if it is applicable directly yet
> to some splitter to generate your usecase, but I guess we could alter
> NoneSplitter to spit out 'the other' part as a testing part
>
>
>> I realize we could have set up custom dataset chunks ourselves or
>> created a CustomSplitter, but what do folks think of extending the
>> HalfSplitter into an NSplitter, where you specify how many pieces you
>> want to split your data into.
>
> hm... is that wording wrong or me is slow? are you saying that you want
> to generate splits which consistn more than of 2 parts? like 1 for training,
> 2nd for testing and parameter selection and 3rd one for resultant
> cross-validation?
>
>>  Obviously, providing N=2 would be
>> identical to the HalfSplitter.  But this would make it really easy to
>> split your data into arbitrary numbers of equal-sized chunks.
>
> yeah... I guess those parameters described above is what you are looking
> for... I am just not sure now if we have that "TheOtherSplitter" which
> toseses
> what wasn't selected into a testing part... may be it is already there ;)
>
> or did I misunderstood smth?
>
> P.S. how is pyepl release coming? ;)
>
> --
> Yaroslav Halchenko
> Research Assistant, Psychology Department, Rutgers-Newark
> Student  Ph.D. @ CS Dept. NJIT
> Office: (973) 353-1412 | FWD: 82823 | Fax: (973) 353-1171
>         101 Warren Str, Smith Hall, Rm 4-105, Newark NJ 07102
> WWW:     http://www.linkedin.com/in/yarik
>
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