Sent from my iPod
On 01.02.2012, at 15:43, Mathieu Blondel math...@mblondel.org wrote:
On Wed, Feb 1, 2012 at 10:10 PM, David Warde-Farley
warde...@iro.umontreal.ca wrote:
I might suggest mean over training examples but sum over output dimensions,
if there is more than one.
Currently,
sorry, I don't have a Windows system at the
moment, if you have a VM could you do it? If you're not set up either,
I'll do it in a day or two.
Best,
Vlad
Sent from my iPod
On 27.01.2012, at 12:29, Fabian Pedregosa fabian.pedreg...@inria.fr wrote:
@vene: do you have time to make the windows
My pleasure, I'm sorry for the delay!
Sent from my iPod
On 27.01.2012, at 20:49, Vincent Dubourg vincent.dubo...@gmail.com wrote:
Thank you Vlad! After a slight upgrade of both numpy and scipy I managed
to get a brand new working 0.10 sklearn!
On 27/01/2012 17:32, Gael Varoquaux wrote:
On
I am quoting from http://docs.python.org/distutils/builtdist.html
By default the installer will display the cool “Python Powered”
logo when it is run, but you can also supply your own 152x261
bitmap which must be a Windows .bmpfile with the --bitmap option.
I'm assuming -b is short for
On Jan 18, 2012, at 20:23 , Andreas wrote:
On 01/18/2012 07:19 PM, Vlad Niculae wrote:
I am quoting from http://docs.python.org/distutils/builtdist.html
By default the installer will display the cool “Python Powered”
logo when it is run, but you can also supply your own 152x261
bitmap
On Jan 19, 2012, at 00:23 , Gael Varoquaux wrote:
On Wed, Jan 18, 2012 at 07:37:12PM +0900, Mathieu Blondel wrote:
It would be nice if you could make a few contributions to scikit-learn
before the application process starts. This will allow you to
familiarize with the code base, us to
Short answer, no.
sparse_encode is just a wrapper for funcionality that existed in the
scikit already (lasso, omp), with support for parallelization. We
couldn't embed SPAMS anyway, because of the license IIRC.
A benchmark would be interesting indeed.
Vlad
On 09.01.2012, at 18:02, Ian
Olivier's solution sounds good.
And it's easy to implement too :) @pprett can you confirm it solves
your perf issue on your data?
I'm talking without actually looking at the code but as long as after fit, the
array will only be needed in F-order, this feels right. However afaik
A bit off topic but since we're talking about work on the SVM module, I noticed
something wrong with the docs.
http://scikit-learn.org/dev/modules/svm.html#tips-on-practical-use
The scaling part makes reference to some Cookbook (I don't know what this is,
it probably died before I joined you
Hello all, especially Fabian.
I've noticed that the new examples still don't show up in
scikit-learn.org/dev/, in particular the multi-label one that I'd like to show
off. Can somebody address this?
Sorry if this should be discussed somewhere else.
Best,
Vlad
On Jan 6, 2012, at 17:39 , Olivier Grisel wrote:
2012/1/6 Vlad Niculae zephy...@gmail.com:
Hello all, especially Fabian.
I've noticed that the new examples still don't show up in
scikit-learn.org/dev/, in particular the multi-label one that I'd like to
show off. Can somebody address
Hello everybody,
This is something that has been bugging me for a while. I am not exactly sure
what entity is printing these messages (I assume joblib) but when doing a
verbose CV with n_jobs=1, the progress report looks something like:
[Parallel(n_jobs=1)]: Done job 20 | elapsed: 28.3s
On Jan 5, 2012, at 23:45 , Fabian Pedregosa wrote:
and that was
quite convenient for testing on systems on which nosetest fails
(windows).
Hi Fabian
Could you please be more specific regarding this point, since as a former
Windows user, I find that I don't know what you mean.
On topic, I
On Jan 3, 2012, at 17:02 , Olivier Grisel wrote:
2012/1/3 Lars Buitinck l.j.buiti...@uva.nl:
We probably need to extend the sklearn.feature_extraction.text package
to make it more user friendly to work with with pure categorical
features occurrences:
I'm not sure this belongs in
On Dec 8, 2011, at 20:11 , David Warde-Farley wrote:
On Tue, Nov 15, 2011 at 03:13:53AM +0900, Mathieu Blondel wrote:
Hi,
Thanks heaps Gael. I'm planning to contact the guy by tomorrow. I
think it would be easier for him if we don't contact him individually.
I can make the reservations
I think I know what happened here.
An upstream change in scipy removed scipy.lena() and left only
scipy.misc.lena().
I wonder if this affects other examples as well. I will try to check
and patch this soon.
Vlad
On Wed, Dec 7, 2011 at 1:38 PM, Gael Varoquaux
gael.varoqu...@normalesup.org
On Dec 6, 2011, at 11:04 , Gael Varoquaux wrote:
On Tue, Dec 06, 2011 at 09:41:56AM +0200, Vlad Niculae wrote:
This is actually exactly how the module is designed.
Great design! I should have looked at it closer before writing my mail.
We have BaseDictionaryLearning which only implements
On Tue, Dec 6, 2011 at 11:46 PM, Alexandre Gramfort
alexandre.gramf...@inria.fr wrote:
I do confirm that Lasso and LassoLars both minimize
1/2n || y - Xw || + alpha ||w||_1
and that the n should not be present in the sparse coding context.
it means :
On Tue, Nov 29, 2011 at 10:02 PM, Alexandre Gramfort
alexandre.gramf...@inria.fr wrote:
Hi Alex,
I would say:
if it makes sense to fit a GP with only one point:
it should be fixed
Note that even though it might not make any sense in practice, unless
there's a mathematical reason that I'm
Hi Olivier,
This is very cool. Could we plot average test coverage as well, similar to pep8?
Is there a way to subscribe to the build reports, like with the
buildbot? I signed up but still couldn't find one.
Vlad
On Mon, Nov 28, 2011 at 4:26 AM, Olivier Grisel
olivier.gri...@ensta.org wrote:
Hello Massimo
I believe this is an issue others, including me, have faced:
https://github.com/scikit-learn/scikit-learn/issues/445
https://github.com/scikit-learn/scikit-learn/issues/330
I reverted to the stable versions of numpy and scipy from their
website, and the bleeding-edge scikit-learn,
On Mon, Nov 21, 2011 at 2:08 PM, Lars Buitinck l.j.buiti...@uva.nl wrote:
2011/11/21 Jacob VanderPlas vanderp...@astro.washington.edu:
I would recommend these: I'm currently taking the Machine Learning
course, taught by Andrew Ng, which will be offered again in January.
It's been a great intro
Gael, can you give me the info (URL and telephone number) for the
guest house? I would like to call them to make a reservation for me. I
can make a reservation for other people too at the same time if needed
(since Gael only reserved for 5 people).
Yes and maybe we can benefit from Fabian's
Very much +1, I would always cringe when seeing colormesh calls.
I gave a talk using the IPython notebook and scikit-learn examples,
setting it to SVG mode at the top, and I would have to switch back to
PNG mode for all examples using pcolormesh because it would crash
(well probably just take
Yes, I was thinking of a sequencial, exploratory IPython-style thing
where you change something in your X and re-fit, when you don't want
to clone and delete the old estimator. Hope this makes sense.
Vlad
2011/11/6 Lars Buitinck l.j.buiti...@uva.nl:
2011/11/6 Vlad Niculae v...@vene.ro
On Fri, Nov 4, 2011 at 4:54 PM, Andreas Müller amuel...@ais.uni-bonn.de wrote:
On 11/04/2011 03:49 PM, Andreas Müller wrote:
On 11/04/2011 03:42 PM, Alexandre Passos wrote:
On Fri, Nov 4, 2011 at 10:34, Lars Buitinck l.j.buiti...@uva.nl wrote:
2011/11/4 Alexandre Passos alexandre...@gmail.com:
Interesting. I've been staring at the code but the algorithm itself
shouldn't be losing precision. On the other hand, there are those
stopping conditions that I had taken from the C implementation of
the author of the Cholesky-OMP paper. If it's as you say, it could be
that when it fails, OMP
Hi Jake,
A while back I remember having that issue because my local version of
sphinx was higher than 1.0.0 and thus unsupported by the scikit-learn
docs, so the function links wouldn't work when I built it locally, but
they would work in the online-generated version.
Did the sphinx version used
Thank you for the observation. I have been looking into this since
yesterday where the same thing has been reported on my blog by Bob L.
Strum. At the moment I have no idea what the cause is. Does it behave
in the same way if you use the gram solver instead?
Best,
Vlad
On Tue, Oct 18, 2011 at
Hello
As far as I can tell (hope I'm not too tired and missing something),
gaussian processes are missing from the class reference. They are not
included in the classes.rst index.
Is this just an omission? Because the module seems to have solid
docstrings that deserve to be listed.
Best,
Vlad
I think that the binaries without statically linked libgcc and
libstdc++ would have worked if run from a mingw32 environment (ie.
they worked in mine). I wonder if it works the other way around (ie.
no static linking, build with MSVC, run from within mingw32)
Fabian, is the 0.8 release built with
Hopefully the positive reports from the initial discussion are
actually accurate and the new installers are working.
As far as I can tell, sourceforge still hosts the old, buggy
installers. (looking at the date)
If this turns out to be the case, who can update the sourceforge files?
Vlad
On
can be closed and I can be
rehabilitated in the public eye :)
Best,
Vlad
On Sat, Sep 24, 2011 at 3:25 PM, josef.p...@gmail.com wrote:
On Sat, Sep 24, 2011 at 8:08 AM, Vlad Niculae v...@vene.ro wrote:
The date should be 24th I think since I uploaded it late at night.
You can get it from PyPI
201 - 233 of 233 matches
Mail list logo
