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/ CrossValidatedTransferError?
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, James M. Hughes wrote:
Ok, so I'm really confused now why my code doesn't work, as I thought I
had it figured out. I'm going to post the code, then my understanding of
what it does, then hopefully we can sort this out.
On Nov 19, 2008, at 10:15 AM, Yaroslav Halchenko wrote:
To do RFE
named _tkinter, please install the python-tk
package
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), 0.32408280922431854,
0.01858597917627762, array(-0.45317547552735754), -0.44109126548914901)
if it is similar, then problem just in plotting...
On Mon, 08 Dec 2008, Dornisch, John wrote:
Yes...
On 12/8/08 9:30 AM, Yaroslav Halchenko [EMAIL PROTECTED]
wrote:
weird... btw -- did you mean
is the host machine for your VM?
What settings are you using for your virtual machine (RAM, Diskspace,...)?
Which version of Ubuntu are you running?
What does 'uname -a' ran in a console inside the VM give you?
What is 'extremely slow' in seconds (or minutes)? ;-)
Michael
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of a full
cross-validation) and running into an error
as is shown in the attached file.
Can anyone help me with figuring this out?
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just remembered, they also offer free licenses for open source software
developers :)
http://www.wingware.com/store/prices
AAA -- don't do this to us ;-)
ok... let see... ;-)))
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?
Below is the full code that I modified the one in the example.
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Is that what you are looking for?
Looking forward to your feedback,
Michael
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as far as I've understood - it could be of interest because of
the models provided: mainly neural networks (most probably the
reason behind brain) and reinforcement learning, which
are currently missing in PyMVPA.
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center_ids! ;) in any case, alternative metric
needs to be used, so for each center_id it lists not the spherical
neighbors, but entries with the same ROI id... then searchlight indeed
would be a native thing to use directly ;)
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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? ;)
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for one thing. I
have attached a .png of the plot. I tried upgrading matplotlib (from
0.98.3 to 0.98.5) but that doesn't change anything.
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for this dataset).
Best,
P
2009/3/28 Yaroslav Halchenko deb...@onerussian.com:
Hypothesis:
I think that one of the possible causes for such behavior is whenever
your features are not normed to lie approximately in the same range...
assume that you have one which is 100 and the rest
=0.84023 min=-1.23648 max=43.8952
yeah -- that is why it is the first one reported ;)
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could periodically merge you in or cherry pick...
On Fri, 27 Mar 2009, Valentin Haenel wrote:
patch attached.
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considerably and makes it
possible to ship it for unittests without causing too much traffic
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to be minimal work - not including stuff
copied from from SVM, I'm only looking at a handful of lines of code. I
love python :)
Thoughts? Sorry for the wind...
Btw yarik -- congratulations!!
-s
Yaroslav Halchenko wrote:
heh heh... indeed... phd defense tomorrow... computers
). If there is no feature selection, than,
permutation testing F- or converted z-scores might be also a nice one.
In both cases though you need to decide on the thresholding scheme ;)
I hope this helps
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from moving the
dataset loop inside of searchlight in comparison to a simple outer loop
(in terms of speed)? I guess it could be quite a bit...
Oppinions?
Michael
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to searchlight, some of the patches might need to
be discussed -- there could be a better way to accomplish the mission ;)
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) with
make unittests
to assure that everything works fine, and debugging output doesn't
crash, etc
as for upstream -- did you mean us? or libsvm?
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;)
Yeah i agree. I kinda understand your idea, but i wouldn't know how to write
the
code :-(
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fix, and then send the new version.
since you didn't yet push your changes anywhere you indeed might simply
do evil rebases until you think you are done. It might be worth
considering using topgit [1] to take care about such feature-branches...
?
[1] http://repo.or.cz/w/topgit.git
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LinearSVMWeights for now... I will let
you know whenever it is done
Oh great! Thank you very much for putting so much work into this!
working on it... although on the way stumbled upon some other elderly
code which needed some attention ;)
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correspond to the labels reported by
dataset.uniquelabels, but I've not done explicit testing for that yet --
so please be cautious ;) it is just that libsvm decides on its own order
-- I think I took care of mapping it back into original order, but who
knows ;)
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Research
2.
http://www.pymvpa.org/faq.html#how-do-i-know-which-features-were-finally-selected-by-a-classifier-doing-feature-selection
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the comp_smlr_svm.py example script to read in a set of
NiftiImages (some zstats I had laying around).
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way you
do it) should have a matching dimension
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for this purpose cause it takes
the maximum boxlengths for all events.
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oops -- forgotten the mailing list
On Sun, 04 Oct 2009, Yaroslav Halchenko wrote:
do you have rpy running?
what version of pymvpa? if = 0.4.3 what does
mvpa.wtf()
says? ;)
On Sun, 04 Oct 2009, patrik andersson wrote:
Hi,
I wonder what I need to do to have access to glmnet. When
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just plot 1 voxel (which later carries perfect correlation)
before/after detrend?
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quickie answer -- SVM does multiclass via pair-wise... so there are 3
classifiers for 3-class classification: 1-vs-2, 1-vs-3, 2-vs-3.
Therefore you are getting 3 sensitivities correspondingly ;)
so it is not even 1 per condition, which would be in the case with SMLR
On Sun, 15 Nov 2009, Mark
Lets return back to the mailing list ;) might be of interest to public
In general, classifier with RFE should behave as any other classifier...
See attached your exact code to use RFE-ed classifier (I've just changed
proportion to be removed to 50%, and enabling debugging output so
we could get
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Thanks to James we have it!
See below
- Forwarded message from James Kyle jamesk...@macports.org -
Date: Wed, 25 Nov 2009 08:34:54 -0800
From: James Kyle jamesk...@macports.org
To: Yaroslav Halchenko y...@dartmouth.edu
Subject: Re: [pymvpa] Fwd: mvpa
X-CRM114-Status: UNSURE (8.1422
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On Tue, 15 Dec 2009, Matthias Ekman wrote:
mmh... OK I see. Thanks for clarifying this point.
Not a PyMVPA related question, but do you think one could handle the
limited amount of RAM (PS3) with an external flash-drive working as
swap?
well... of cause everything depends on the tasks/goals,
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more information to be able to help you.
Michael
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moreover, since it could have been addressed on a server side as well --
it had been -- so now you should have no problem even using 1.6.6 ;-)
On Thu, 21 Jan 2010, Yaroslav Halchenko wrote:
Hi, just a little update
Problem with git (client side) of 1.6.6 has been localized, solution
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at chance
(i.e. 0.5 since I did binary classification).
how does your cv.states.null_dist.dist_samples would look? ;)
On Wed, 27 Jan 2010, Yaroslav Halchenko wrote:
could you share more details about your data? number of labels/samples?
what error are you getting from cv (may be confusion matrix
the importance/effect
of feature selection and congrats on obtaining good results ;)
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http://en.wikipedia.org/wiki/Oops
2nd definition is the closest:
A small accident
On Tue, 02 Feb 2010, sergey.v.fogel...@dartmouth.edu wrote:
oops?
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of testing :-/
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switch:
2010/2/3 Yaroslav Halchenko li...@onerussian.com:
I wonder if you could help me out with testing either building works
Also, if you have system wide installed libsvm it would be great if you
tested it with
--with-system-libsvm
build and install commands.
cbu
On Wed, 10 Feb 2010, Yaroslav Halchenko wrote:
in 0.5.x branch. rpy2 debian package depends on more recent R release
(2.10) so I would need to check if it is indeed a strict requirement.
But you should be all set now to use glmnet from 0.4 branch.
and now python-rpy2 should also
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()
to see if no objections from filesystem ;)
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in a gesture of gratitude to Francisco for
the nice references ;)
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Symmetric Polyhedron
I can share mine if interested.
sure!
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On Tue, 16 Mar 2010, Yaroslav Halchenko wrote:
the design, preprocessing, temporal compression, etc. But if
performance with these random runs is about the same as
partitioning on the actual runs I feel safer moving to a
non-run-partitioning scheme.
that sounds like a good idea!
Now
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again range is quite outstanding)
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Description: Digital signature
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correspond to a 4D NiftiImage instance.
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CorrErrorFx by
default for regressions.
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