Hi Ronnie,

I have never used Theano, could you be a little more specific ? What do you
want to compute ? What is your input data ? Basically, all these metrics
are independant of the scikit and take numpy arrays as input so you can use
it with any data under this format.

Now, if you want to integrate some online computation directly into Theano,
this is another story...

Alexandre.


On Sun, May 12, 2013 at 4:35 PM, Ronnie Ghose <ronnie.gh...@gmail.com>wrote:

> uhhh +1. any chance of using theano with it?
>
>
> On Sun, May 12, 2013 at 7:35 AM, Alexandre ABRAHAM <
> abraham.alexan...@gmail.com> wrote:
>
>> Hey scikit people,
>>
>> I know that the first purpose of scikit is not to handle big data but
>> would you be interested by a PR of my silhouette block implementation ? My
>> benches have shown that it is a bit slower than the scikit one when data is
>> small but it divides memory usage by n_cluster ^ 2. Plus it can be
>> parallelized. But, obviously, the code is less readable.
>>
>> I am currently working with data that does not fit in memory so I try to
>> minimize its usage as much as I can. I have also implemented an online
>> variance (and explained variance) object based on [Chan79] approach (there
>> may be better ones, I haven't checked). This is not hard to code but it can
>> be useful for some people.
>>
>> Alexandre.
>>
>> [Chan79] "Updating Formulae and a Pairwise Algorithm for Computing Sample
>> Variances." Chan 79
>>
>>
>>
>> On Fri, May 10, 2013 at 6:26 PM, Bao Thien <ntba...@gmail.com> wrote:
>>
>>> Hi Alexandre,
>>>
>>> It sounds very great. I will try it and let you know soon.
>>>
>>> Regards,
>>>
>>> T.Bao
>>>
>>>
>>> On Fri, May 10, 2013 at 6:19 PM, Alexandre ABRAHAM <
>>> abraham.alexan...@gmail.com> wrote:
>>>
>>>> Bao,
>>>>
>>>> Sorry for the delay. I have push a new version of the code on the gist
>>>> (there is now a n_jobs keyword parameter). It should use a bit more memory.
>>>>
>>>> Fast bench (see main in the gist) :
>>>> Scikit silhouette (113.294149s): -0.013992
>>>> Block silhouette (23.485517s): -0.013992
>>>> Block silhouette parallel (23.351142s): -0.013992
>>>>
>>>> I only have 2 cores so this is not very significant. If you have more,
>>>> feedback is welcome !
>>>>
>>>> Alexandre.
>>>>
>>>>
>>>>
>>>>
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>>>> Learn Graph Databases - Download FREE O'Reilly Book
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>>>
>>>
>>> --
>>> Nguyen Thien Bao
>>>
>>> NeuroInformatics Laboratory (NILab),
>>> Fondazione Bruno Kessler (FBK), Trento, Italy
>>>  Centro Interdipartimentale Mente e Cervello (CIMeC)
>>> Universit`a degli Studi di Trento, Italy
>>> Email: ntba...@gmail.com  or  ntbao...@yahoo.com
>>> Cellphone: +39.345.293.1006 (Italy)
>>> Cellphone: +84.996.352.452 (VietNam)
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Learn Graph Databases - Download FREE O'Reilly Book
>>> "Graph Databases" is the definitive new guide to graph databases and
>>> their applications. This 200-page book is written by three acclaimed
>>> leaders in the field. The early access version is available now.
>>> Download your free book today! http://p.sf.net/sfu/neotech_d2d_may
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>>
>>
>> ------------------------------------------------------------------------------
>> Learn Graph Databases - Download FREE O'Reilly Book
>> "Graph Databases" is the definitive new guide to graph databases and
>> their applications. This 200-page book is written by three acclaimed
>> leaders in the field. The early access version is available now.
>> Download your free book today! http://p.sf.net/sfu/neotech_d2d_may
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>
>
> ------------------------------------------------------------------------------
> Learn Graph Databases - Download FREE O'Reilly Book
> "Graph Databases" is the definitive new guide to graph databases and
> their applications. This 200-page book is written by three acclaimed
> leaders in the field. The early access version is available now.
> Download your free book today! http://p.sf.net/sfu/neotech_d2d_may
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>
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"Graph Databases" is the definitive new guide to graph databases and 
their applications. This 200-page book is written by three acclaimed 
leaders in the field. The early access version is available now. 
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