Hi,
I have used scikit-learn for academic purposes and I like it very much.
I want to contribute to it. I have gone through the developers
documentation and setup my local working directory.
As suggested in the developers documentation, it did look for some EASY
tagged issues in the issue
I recently contributed a fix to numpy master (to be part of numpy
1.9.0) to use nditer API to stream buffers to non-'file' file object:
https://github.com/numpy/numpy/pull/4077
That should make it possible to refactor joblib to stream pickled data
to GzipFile instances or use the
2014/2/2 Jitesh Khandelwal jk231...@gmail.com:
Hi,
I have used scikit-learn for academic purposes and I like it very much.
I want to contribute to it. I have gone through the developers documentation
and setup my local working directory.
As suggested in the developers documentation, it did
Hi,
I want to know whether there are algorithms on Recommender Systems
in scikit-learn. I didn't found this topic in documentation. If not, I
would like to contribute on this topic.
Please guide me.
Thanks !!
Glad to see this thread revived!
Sklearn-users who are interested in this stuff should check out Hyperopt's
sklearn interface:
https://github.com/hyperopt/hyperopt-sklearn
It's very much a work-in-progress. We're in the process of putting together
some examples / tutorial, and a tech report
(Sorry about the comment about a revived thread, I was thinking of another
one!)
On Sun, Feb 2, 2014 at 10:43 AM, James Bergstra james.bergs...@gmail.comwrote:
Glad to see this thread revived!
Sklearn-users who are interested in this stuff should check out Hyperopt's
sklearn interface:
Hi Mit.
Some of the algorithms in scikit-learn could be use for recommender
systems, but there is no estimator for that.
We are currently hesistant in increasing the scope of scikit-learn, as
the core contributors are busy doing maintenance,
and we would rather focus on a stable 1.0 release.
On 02/02/2014 12:06 PM, Olivier Grisel wrote:
Note: the name of the project is scikit-learn, not scikit or SciKit
nor sci-kit learn. Cheers,
I should make this my signature from now on. Also including
pronounciation (sy-kit learn)
On 02/01/2014 10:42 PM, Robert Layton wrote:
Finally, when choosing classifiers, it's our preference to focus on
heavily used classifiers, rather than state of the art. Many of the
core devs (and myself) have coded classifiers that are scikit-learn
compatible, but not in the library
I've heard stchee-kit once, along with stchee-pee and num-pee.
Vlad
On Sun Feb 2 18:39:58 2014, Hadayat Seddiqi wrote:
i always said skikit
On Sun, Feb 2, 2014 at 12:20 PM, Andy t3k...@gmail.com
mailto:t3k...@gmail.com wrote:
On 02/02/2014 12:06 PM, Olivier Grisel wrote:
Note:
On 02/02/2014 06:39 PM, Hadayat Seddiqi wrote:
i always said skikit
Many people do ;)
sci as in science =)
--
WatchGuard Dimension instantly turns raw network data into actionable
security intelligence. It gives you
On 02/02/2014 07:41 PM, Vlad Niculae wrote:
I've heard stchee-kit once, along with stchee-pee and num-pee.
We should have an FAQ.
It should include
What is the project name? scikit-learn, not scikit or SciKit nor sci-kit
learn.
How do you pronounce the project name? sy-kit learn. sci stands
On 01/30/2014 11:31 PM, Sturla Molden wrote:
Lars Buitinck larsm...@gmail.com wrote:
But anyway, the modification has not been implemented in scikit-learn
because the combination of OpenMP and Python multiprocessing is rather
problematic.
This is actually a GNU problem. libgomp cannot be
On 01/31/2014 09:50 AM, Gael Varoquaux wrote:
if not isinstance(score, numbers.Number):
raise ValueError(scoring must return a number, got %s (%s)
instead. % (str(score), type(score)))
I am not opposed to making this check more relaxed: we could add an 'or
Hi Manoj.
Unfortunately I can not give you any advice at the moment. I am way to
swamped to take care of GSoC :-/
I think in both clustering and linear models there is a lot of room for
improvement.
For clustering there was BIRCH (that's the name, right?) that I think
Olivier wanted to
Awesome - thanks guys!
@Gael: I'll look into the single file storage and submit a PR
2014-02-02 Olivier Grisel olivier.gri...@ensta.org:
I recently contributed a fix to numpy master (to be part of numpy
1.9.0) to use nditer API to stream buffers to non-'file' file object:
On 01/17/2014 04:24 PM, Arnaud Joly wrote:
Thanks !!!
I have updated the pdf (http://static.ajoly.org/files/poster.pdf)
and added the missing authors (and all scikit-learn contributors).
Best,
Arnaud
Before looking at the poster I though so how is he gonna fit hundreds
of names on there?
AWESOME!!!
Thank you so much for working on this!
Cheers,
Andy
On 01/17/2014 12:08 AM, Olivier Grisel wrote:
Hi all,
Jaques and I have recently been working on moving the dev
documentation build job out of Fabian's workstation to a server on the
public Rackspace Cloud.
The deployment of
On Sun, Feb 2, 2014 at 5:26 PM, Joel Nothman joel.noth...@gmail.com wrote:
Nice. I've taken a look at what you've got there...
So for example, to draw a randomised SVC instance:
from hpsklearn.components import svc
from hyperopt.pyll.stochastic import sample
sample(svc(str))
Andy t3k...@gmail.com wrote:
I did not really understand this before. Does that mean that we can
never have OpenMP + joblib?
A new patch was submitted to libgomp today, so we'll just have to wait and
see.
http://gcc.gnu.org/bugzilla/show_bug.cgi?id=60035
I am not sure the GOMP team really
This is in response to the thread on recommender system implementation in
scikit-learn. I would also like to know if any of the scikit-learn contributors
are willing to mentor a project which implements basic recommender system
algorithms - collaborative filtering (user-based/item-based/matrix
On Mon, Feb 3, 2014 at 5:49 AM, Andy t3k...@gmail.com wrote:
We should have an FAQ.
It should include
What is the project name? scikit-learn, not scikit or SciKit nor sci-kit
learn.
How do you pronounce the project name? sy-kit learn. sci stands for
science!
Do you want to add this
Hi to all,
I want to use KPCA with fit_inverse_transform=True.
Question:
What is the easiest way to test other kernels, aside from the ones
available in the metrics package, keeping in mind that I need the pre-image
(inverse) option?
I noticed that GPy has a wide range of kernels and the option
There have been many people asking about contributing recommender systems
to scikit-learn, and generally the response has been that it doesn't quite
fit in with the library. Though it can be shoehorned somewhat perhaps, I
recommend you take a look at https://github.com/mendeley/mrec, which
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