[pymvpa] custom partitioner
wolfgang.m.pauli at gmail.com
Wed May 18 07:30:01 UTC 2016
Thank you for the explanation. This makes sense now. It was working well
within Cross-validation, but when I was calling Splitter later for a manual
sensitivity analysis, for which I had found a code snippet, the analysis
was using partitions 0 1 instead. So I got very different results during
cross-validation, in comparison to the later sensitivity analysis.
On Tue, May 17, 2016 at 7:26 PM, Yaroslav Halchenko <debian at onerussian.com>
> On Tue, 17 May 2016, Wolfgang Pauli wrote:
> > Hi,
> > I think I just had a shocking revelation. I tried to do cross validation
> > with a custom partitioner like so:
> > splt_rule = [([0,1],[6,7]),([1,2],[4,7]),([2,3],[4,5]),([3,0],[5,6])]
> > partitioner = CustomPartitioner(splitrule=splt_rule, attr='chunks')
> > For example, i thought the classifier would be trained on chunks 0 and 1,
> > and tested on 6 and 7. during cross-validation. However, when I used
> > actually generated the partitions and looked which chunks are in each
> > partition, I found that the partitioner would actually create three
> > partitions, two as specified by the split rule, and one containing the
> > remaining chunks.
> > I.e. instead of getting e.g. [0,1],[6,7], I would get ([2, 3, 4,
> > 5],[0,1],[6,7]).
> > Is this correct? How can I keep it from creating that third partition
> > the remaining items?
> well, in general partitioners are implemented so they don't cause any
> memory impact and are fast... for that they just assign partitioning as
> a new sample attribute, and do not split dataset into partitions. That
> job is later done by Splitter, e.g. within CrossValidation. Within
> CrossValidation, that splitter cares only about partitions labeled as 1
> (for training) and 2 (for testing). The others it ignores.
> If you really need to select those partitions 1 and 2 asap, I guess just
> use smth like
> partitioned_ds.select(partitions=[1, 2])
> Yaroslav O. Halchenko
> Center for Open Neuroscience http://centerforopenneuroscience.org
> 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
> Pkg-ExpPsy-PyMVPA mailing list
> Pkg-ExpPsy-PyMVPA at lists.alioth.debian.org
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