Hi Kemal,
Thanks a lot for the modifications. The introduction is now much better and
the figure is really helpful to visualize what biclustering can do!
Some further comments...
To keep the "proposal timeline" section more concise and focused on your
schedule during the summer, I would move the
On Mon, Apr 29, 2013 at 12:45:44PM +0800, xinfan meng wrote:
> Just FYI, Wikipedia treats bi-clustering and co-clustering as the same
> algorithm. And the name "co-clustering" is more popular in my opinion.
Agreed.
> This paper describe the most well-known co-clustering algorithm and has
> 888 ci
H, Eren,
Just FYI, Wikipedia treats bi-clustering and co-clustering as the same
algorithm. And the name "co-clustering" is more popular in my opinion. This
paper describe the most well-known co-clustering algorithm and has 888
citations: Co-clustering documents and words using bipartite spectral g
Congrats Robert!
On Sun, Apr 28, 2013 at 7:56 AM, Robert Layton wrote:
> I just received some good news. My talk "scikit-learn, machine learning
> and cybercrime attribution" has been accepted!
>
> I'll be presenting between the 5th and 7th of July. For those that missed
> the previous emails,
Good work, congratulations!
vlad
On Mon, Apr 29, 2013 at 11:34 AM, Satrajit Ghosh wrote:
> congrats robert. if you can post the slides on speakerdeck or some such
> platform, that would be great.
>
> cheers,
>
> satra
>
> On Sun, Apr 28, 2013 at 7:56 AM, Robert Layton
> wrote:
>>
>> I just rece
congrats robert. if you can post the slides on speakerdeck or some such
platform, that would be great.
cheers,
satra
On Sun, Apr 28, 2013 at 7:56 AM, Robert Layton wrote:
> I just received some good news. My talk "scikit-learn, machine learning
> and cybercrime attribution" has been accepted!
>
Great! Congratulations!
Mathieu
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Hi again,
For collaborative filtering: www.stat.osu.edu/~dmsl/Sarwar_2001.pdf
For association rule learning:
http://rakesh.agrawal-family.com/papers/vldb94apriori.pdf
And as the schedule part:
- Getting familiar with scikit-learn, API structure etc. (1 week)
- Generating, finding datasets
On Sun, Apr 28, 2013 at 07:15:10PM +0200, Kemal Eren wrote:
> Regarding nimfa: I was suggesting using it as a dependency, not copying and
> pasting their code. Is that not a possibility?
No. For 2 reasons. The first one is that we do not want to increase our
dependency list. The second is that a B
> I'm trying to finding out how to determine which entries are used for each
> cross validation test.
Convert the cv object to a list, and you will have the indices of the
train and test set in each fold. You can also use
cross_validation.test_train_split:
http://scikit-learn.org/stable/modules/cr
On Sun, Apr 28, 2013 at 08:06:11PM +0200, Richard Cubek wrote:
> how stable the python binding is regarding the website issue mentioned
> above.
Faily stable I would say. The remarks applied years ago.
> So is there any method within scikit, that could help me finding a
> feature mapping?
I am n
I'm trying to finding out how to determine which entries are used for each
cross validation test. I do not know how to find out which entries are used
for each cross validation test. The gridding result seems to be revealing
some parameter settings to achieve reasonable results despite our previous
Hello everyone,
I'm new to the list so first of all thanks a lot for your work on this
lib!
I need libsvm probability estimates as well as Logistic Regression (LR)
in a three classes problem with a training data set size of about 5-6000
at 20-50 features. I am familiar with python and octave (
For reminder, EuroScipy's deadline for submitting abstracts is tonight !
%
Dear Scientist using Python,
EuroSciPy is the European Conference on Python in Science. The call for
abstracts for oral and poster presentations for EuroSciPy 2013 closes at
the end
of
Hi Mathieu,
Thanks for your feedback. I have been making revisions to my draft,
including changes to address your comments. If you have any more
suggestions I would be glad to hear them.
Regarding nimfa: I was suggesting using it as a dependency, not copying and
pasting their code. Is that not a
> > Actually Fabian was hired in January 2010.
>
> Right. That's correct. Nelle's initial email was right. I just got
> confused because the date of the international sprint were wrong: it was
> in 2011.
>
I've fixed this in my future emails to potential sponsors.
Thanks for letting me know!
N
>
On Sun, Apr 28, 2013 at 06:35:53PM +0200, bthirion wrote:
> Actually Fabian was hired in January 2010.
Right. That's correct. Nelle's initial email was right. I just got
confused because the date of the international sprint were wrong: it was
in 2011.
G
> B
> On 28/04/2013 18:33, Gael Varoquaux
On Sun, Apr 28, 2013 at 06:30:00PM +0200, Nelle Varoquaux wrote:
> Scikit-learn is an easy-to-use and general purpose machine learning toolbox
> written in Python. It provides state-of-the-art implementations of many well
> known machine learning algorithms, while maintaining an easy-to-use interfa
Hi everyone,
As some of you may know, we are organizing an international sprint in Paris
late July. In order for the sprint to be successful, we are looking for
funding. If you are using scikit-learn professionally, please consider
funding the event or advertising the sprint. Here is a brief descr
Hi Kemal,
Below a few comments.
- Please describe in more details what is biclustering and why it is
important. A figure would be nice.
- Can you indicate the citation count of the reference papers you mention?
The higher, the better...
- Binarization is already supported in scikit-learn.
- Missi
Hi scikit-learn team,
As discussed in another thread, I have put together a draft of my proposal
to add biclustering algorithms this summer. Here is the link:
https://docs.google.com/document/d/17v1r5gqnMA6ExmYYxOSBWjfAdQiCc7-Gjm4O_8QtTJs/edit?usp=sharing
Any suggestions are welcome.
Best regar
I just received some good news. My talk "scikit-learn, machine learning and
cybercrime attribution" has been accepted!
I'll be presenting between the 5th and 7th of July. For those that missed
the previous emails, my presentation will be sklearn-centric, with an light
introduction to machine learn
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