Dear Roberto,
Just in case you want to better understand what Sebastian suggested, let me
suggest you two short videos taken from the ML course of Hastie and
Tibshirani
about the shrinkage methods:
https://www.youtube.com/watch?v=cSKzqb0EKS0
https://www.youtube.com/watch?v=A5I1G1MfUmA
They help
Thanks a lot Andreas
On Thu, Apr 9, 2015 at 7:22 PM, Andreas Mueller wrote:
> For vision:
> http://www.matthewzeiler.com/pubs/iccv2011/iccv2011.pdf
> http://people.idsia.ch/~ciresan/data/icann2011.pdf
>
>
> On 04/09/2015 12:56 PM, Eraldo Pomponi wrote:
>
> Dear And
Dear Andy,
On Thu, Apr 9, 2015 at 2:56 PM, Andy wrote:
> Hi Dan.
>
> Scikit-learn focuses on "flat" signals and algorithms and we don't
> usually add algorithms on time-series or nd-data,
> as that would significantly widen the scope and complicate API. Maybe we
> should add this to the FAQ.
>
Thanks Gael,
On Mon, Mar 30, 2015 at 4:16 PM, Gael Varoquaux <
gael.varoqu...@normalesup.org> wrote:
> For such question, the following website is useful:
>
> http://www.downforeveryoneorjustme.com/scikit-learn.com
>
>
I didn't know about this website.
Cheers,
Eraldo
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Eraldo
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Dear ML experts,
I'm solving a multi-class classification problem. Following the great
advice of Peter Prettenhofer and Gilles Louppe (
http://www.slideshare.net/DataRobot/gradient-boosted-regression-trees-in-scikitlearn)
about the use of the GradientBoostingClassifier (after tuning the
iperparam.
Dear Roberto,
On Wed, Sep 24, 2014 at 12:14 AM, Pagliari, Roberto wrote:
> I’m using a pipeline with gridsearchcv. I tried this to allow search over
> a range of number of trees
>
>
>
> params = dict(random_forest_classifier__n_estimators=[8, 9, 10, 11])
>
> clf = grid_search.GridSearchCV(my_pip
Thanks a lot ... I'm in too [?]
Cheers,
Eraldo
On Tue, Nov 26, 2013 at 9:56 PM, Jaques Grobler wrote:
> Thanks for the share +1
>
>
> 2013/11/26 Sam Bessalah
>
>> Cant wait for you to teach me some R Olivier ;)
>> I enrolled ;)
>>
>> Sam Bessalah
>>
>> > On Nov 26, 2013, at 7:04 PM, Olivier G
Dear Paolo,
> If that is your question I can share my code.
> :-)
Sorry if I'm hijacking this tread but, if it is public, I would like to
have a look at your code.
Thanks a lot.
Cheers,
Eraldo
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