[scikit-learn] Does random forest work if there are very few features?

[lampahome]

I read doc and know tree-based model is determined by entropy or gini
impurity.

When model try to create leaf nodes, it will determine based on the
feature, right?

Ex:
I have 2 features A,B, and I divide it with A.
So I have left and right nodes based on A.
It should have the best shape if I create nodes based on A, right?

Now if I have 100 estimators but I only have two features, do I have
different trees which are all based on feature A?
or the shape of trees based on A are all the same cuz they were created by
feature A?

thx
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Re: [scikit-learn] Next Sprint

[Alexandre Gramfort]

ok for me

Alex

On Thu, Dec 20, 2018 at 8:35 PM Adrin  wrote:
>
> It'll be the least favourable week of February for me, but I can make do.
>
> On Thu, 20 Dec 2018 at 18:45 Andreas Mueller  wrote:
>>
>> Works for me!
>>
>> On 12/19/18 5:33 PM, Gael Varoquaux wrote:
>> > I would propose  the week of Feb 25th, as I heard people say that they
>> > might be available at this time. It is good for many people, or should we
>> > organize a doodle?
>> >
>> > G
>> >
>> > On Wed, Dec 19, 2018 at 05:27:21PM -0500, Andreas Mueller wrote:
>> >> Can we please nail down dates for a sprint?
>> >> On 11/20/18 2:25 PM, Gael Varoquaux wrote:
>> >>> On Tue, Nov 20, 2018 at 08:15:07PM +0100, Olivier Grisel wrote:
>>  We can also do Paris in April / May or June if that's ok with Joel and 
>>  better
>>  for Andreas.
>> >>> Absolutely.
>> >>> My thoughts here are that I want to minimize transportation, partly
>> >>> because flying has a large carbon footprint. Also, for personal reasons,
>> >>> I am not sure that I will be able to make it to Austin in July, but I
>> >>> realize that this is a pretty bad argument.
>> >>> We're happy to try to host in Paris whenever it's most convenient and to
>> >>> try to help with travel for those not in Paris.
>> >>> Gaël
>> >>> ___
>> >>> scikit-learn mailing list
>> >>> scikit-learn@python.org
>> >>> https://mail.python.org/mailman/listinfo/scikit-learn
>> >> ___
>> >> scikit-learn mailing list
>> >> scikit-learn@python.org
>> >> https://mail.python.org/mailman/listinfo/scikit-learn
>>
>> ___
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>
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Re: [scikit-learn] Next Sprint

[Adrin]

It'll be the least favourable week of February for me, but I can make do.

On Thu, 20 Dec 2018 at 18:45 Andreas Mueller  wrote:

> Works for me!
>
> On 12/19/18 5:33 PM, Gael Varoquaux wrote:
> > I would propose  the week of Feb 25th, as I heard people say that they
> > might be available at this time. It is good for many people, or should we
> > organize a doodle?
> >
> > G
> >
> > On Wed, Dec 19, 2018 at 05:27:21PM -0500, Andreas Mueller wrote:
> >> Can we please nail down dates for a sprint?
> >> On 11/20/18 2:25 PM, Gael Varoquaux wrote:
> >>> On Tue, Nov 20, 2018 at 08:15:07PM +0100, Olivier Grisel wrote:
>  We can also do Paris in April / May or June if that's ok with Joel
> and better
>  for Andreas.
> >>> Absolutely.
> >>> My thoughts here are that I want to minimize transportation, partly
> >>> because flying has a large carbon footprint. Also, for personal
> reasons,
> >>> I am not sure that I will be able to make it to Austin in July, but I
> >>> realize that this is a pretty bad argument.
> >>> We're happy to try to host in Paris whenever it's most convenient and
> to
> >>> try to help with travel for those not in Paris.
> >>> Gaël
> >>> ___
> >>> scikit-learn mailing list
> >>> scikit-learn@python.org
> >>> https://mail.python.org/mailman/listinfo/scikit-learn
> >> ___
> >> scikit-learn mailing list
> >> scikit-learn@python.org
> >> https://mail.python.org/mailman/listinfo/scikit-learn
>
> ___
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> scikit-learn@python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
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Re: [scikit-learn] How to keep a model running in memory?

[Roland Hochmuth via scikit-learn]

Hi Liam, I would suggest start out by taking a look at the gRPC quickstart for 
Python at, https://grpc.io/docs/quickstart/python.html and then modifying that 
example to do what you would like.

The Flask server would launch the separate process using multiprocessing. The 
model process would create a gRPC service endpoint. The Flask server would wait 
for the model process to start and then establish a gRPC connection as a client 
to the gRPC service endpoint of the model process. The gRPC service of the 
model process would have methods, such as trainModel or getModelStatus, … When 
an http request occurs on the Flask http server, the server would then invoke 
the gRPC methods in the model process.

I hope that helps.

Regards --Roland


From: Liam Geron 
Date: Thursday, December 20, 2018 at 9:53 AM
To: Roland Hochmuth 
Cc: Scikit-learn mailing list 
Subject: Re: [scikit-learn] How to keep a model running in memory?

Hi Roland,

Thanks for the suggestion! I'll certainly look into gRPC or similar frameworks. 
Currently we have multiprocessing, but it's not used to that same extent. How 
would the second process have a sort of "listener" to respond to incoming 
requests if it is running persistently?

Thanks so much for the help.

Best,
Liam

On Thu, Dec 20, 2018 at 11:12 AM Roland Hochmuth 
mailto:rhochm...@alteryx.com>> wrote:
Hi Liam, Not sure I have the complete context for what you are trying to do, 
but have you considered using Python multiprocessing to start a separate 
process? The lifecycle of that process could start when the Flask server 
starts-up or on the first request. The separate process would load and run the 
model. Depending on what you would like to do, some form of IPC mechanism, such 
as gRPC could be used to control or get updates from the model process.

Regards --Roland


From: scikit-learn 
mailto:alteryx@python.org>>
 on behalf of Aneto mailto:an...@chatdesk.com>>
Reply-To: Scikit-learn mailing list 
mailto:scikit-learn@python.org>>
Date: Thursday, December 20, 2018 at 8:21 AM
To: "scikit-learn@python.org" 
mailto:scikit-learn@python.org>>
Cc: Liam Geron mailto:l...@chatdesk.com>>
Subject: [scikit-learn] How to keep a model running in memory?

Hi scikit learn community,

We currently use scikit-learn for a model that generates predictions on a 
server endpoint. We would like to keep the model running in memory instead of 
having to re-load the model for every new request that comes in to the server.

Can you please point us in the right direction for this? Any tutorials or 
examples.

In case it's helpful, we use Flask for our web server.

Thank you!

Aneto
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Re: [scikit-learn] Next Sprint

[Andreas Mueller]

Works for me!

On 12/19/18 5:33 PM, Gael Varoquaux wrote:

I would propose  the week of Feb 25th, as I heard people say that they
might be available at this time. It is good for many people, or should we
organize a doodle?

G

On Wed, Dec 19, 2018 at 05:27:21PM -0500, Andreas Mueller wrote:

Can we please nail down dates for a sprint?
On 11/20/18 2:25 PM, Gael Varoquaux wrote:

On Tue, Nov 20, 2018 at 08:15:07PM +0100, Olivier Grisel wrote:

We can also do Paris in April / May or June if that's ok with Joel and better
for Andreas.

Absolutely.
My thoughts here are that I want to minimize transportation, partly
because flying has a large carbon footprint. Also, for personal reasons,
I am not sure that I will be able to make it to Austin in July, but I
realize that this is a pretty bad argument.
We're happy to try to host in Paris whenever it's most convenient and to
try to help with travel for those not in Paris.
Gaël
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[scikit-learn] Submission

[이인규]

Leon LEE
leefranc...@gmail.com
Skype: leefrance7979
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Re: [scikit-learn] How to keep a model running in memory?

[Roland Hochmuth via scikit-learn]

Hi Liam, Not sure I have the complete context for what you are trying to do, 
but have you considered using Python multiprocessing to start a separate 
process? The lifecycle of that process could start when the Flask server 
starts-up or on the first request. The separate process would load and run the 
model. Depending on what you would like to do, some form of IPC mechanism, such 
as gRPC could be used to control or get updates from the model process.

Regards --Roland


From: scikit-learn  on 
behalf of Aneto 
Reply-To: Scikit-learn mailing list 
Date: Thursday, December 20, 2018 at 8:21 AM
To: "scikit-learn@python.org" 
Cc: Liam Geron 
Subject: [scikit-learn] How to keep a model running in memory?

Hi scikit learn community,

We currently use scikit-learn for a model that generates predictions on a 
server endpoint. We would like to keep the model running in memory instead of 
having to re-load the model for every new request that comes in to the server.

Can you please point us in the right direction for this? Any tutorials or 
examples.

In case it's helpful, we use Flask for our web server.

Thank you!

Aneto
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[scikit-learn] How to keep a model running in memory?

[Aneto]

Hi scikit learn community,

We currently use scikit-learn for a model that generates predictions on a
server endpoint. We would like to keep the model running in memory instead
of having to re-load the model for every new request that comes in to the
server.

Can you please point us in the right direction for this? Any tutorials or
examples.

In case it's helpful, we use Flask for our web server.

Thank you!

Aneto
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