I would strongly recommend to start with something easier, like issues
labelled 'easy'. Starting with such a big project is most likely going to
lead to you approaching the project in a way that is not well adapted to
scikit-learn, and thus code that does not get merged.
Cheers,
Gaël
On Thu, Sep
Hello everyone,
I have built scikit-learn and I am ready to start coding. Can I get some
pointers on how I could start contributing to the projects I mentioned in
the earlier mail?
Thanks,
Rohit.
On Mon, Sep 7, 2015 at 11:50 AM, Rohit Shinde
wrote:
> Hi Jacob,
>
> I am interested in Global opt
I think all of the ones that I'm thinking of already have an estimator
interface.
On 09/09/2015 04:10 PM, Sebastian Raschka wrote:
> Might sound like a drastic step, but I would suggest a) making the functions
> private and deprecating the public interface. I think this would be easier on
> "n
Might sound like a drastic step, but I would suggest a) making the functions
private and deprecating the public interface. I think this would be easier on
"new" users, and more experienced people would still be able to use them on own
risk. And over time, some of those functions could optionally
Hi all.
A api issue that has been annoying me for some while is that we don't
have common tests for functions.
That means that incompatibilities are only fixed if someone points them
out in an issue, and API changes like
https://github.com/scikit-learn/scikit-learn/pull/5152
I see two possible w
On the other hand, the wikipedia article is pretty succinct about the
definition. It is definitely a sensible definition of a score.
Additionally, the original paper has > 2900 citations on google scholar.
http://www.ncbi.nlm.nih.gov/pubmed/2720055
On Wed, Sep 9, 2015 at 9:24 AM, Alexandre Gramfo
@mblondel I was talking indeed about Pearson correlation.
Unless proven otherwise with examples, I'd stick to Pearson correlation too.
Alex
--
Monitor Your Dynamic Infrastructure at Any Scale With Datadog!
Get real-time
