Take a look at this.
http://scikit-learn.sourceforge.net/stable/tutorial.html#model-persistence
On Sat, Dec 17, 2011 at 1:28 PM, Jieyun Fu <[email protected]> wrote:
> I guess that's the same questions then. How do I *save the model* ?
> Through pickling? Thanks!
>
>
> On Fri, Dec 16, 2011 at 11:48 PM, xinfan meng <[email protected]> wrote:
>
>> Why would you want to set the coefficients manually? If you want to reuse
>> the model, you can always save the model and load it when you want to use
>> it. If you want to train the model in an online setting, I think there is a
>> SGD api for this.
>>
>> On Sat, Dec 17, 2011 at 3:28 AM, Jieyun Fu <[email protected]> wrote:
>>
>>> So I read the scikit-learn package webpate:
>>>
>>>
>>> http://scikit-learn.sourceforge.net/dev/modules/generated/sklearn.linear_model.LogisticRegression.html
>>>
>>> I can use logistic regression to fit the data, and after I obtain an
>>> instance of LogisticRegression, I can use it to classify new data points.
>>> So far so good.
>>>
>>> Is there a way to set the coefficients of LogisticRegression() instance
>>> though? Because after I obtain the trained coefficients, I want to use the
>>> same API to classify new data points. I also don't want to keep retraining
>>> the data to obtain that particular instance that has the coefficients I
>>> want.
>>>
>>> For example, I want to do something like
>>>
>>> lg = LogisticRegression()
>>>
>>> lg.coef_ = [blah blah blah]
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Learn Windows Azure Live! Tuesday, Dec 13, 2011
>>> Microsoft is holding a special Learn Windows Azure training event for
>>> developers. It will provide a great way to learn Windows Azure and what
>>> it
>>> provides. You can attend the event by watching it streamed LIVE online.
>>> Learn more at http://p.sf.net/sfu/ms-windowsazure
>>> _______________________________________________
>>> Scikit-learn-general mailing list
>>> [email protected]
>>> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>>>
>>>
>>
>>
>> --
>> Best Wishes
>> --------------------------------------------
>> Meng Xinfan（蒙新泛）
>> Institute of Computational Linguistics
>> Department of Computer Science & Technology
>> School of Electronic Engineering & Computer Science
>> Peking University
>> Beijing, 100871
>> China
>>
>>
>> ------------------------------------------------------------------------------
>> Learn Windows Azure Live! Tuesday, Dec 13, 2011
>> Microsoft is holding a special Learn Windows Azure training event for
>> developers. It will provide a great way to learn Windows Azure and what it
>> provides. You can attend the event by watching it streamed LIVE online.
>> Learn more at http://p.sf.net/sfu/ms-windowsazure
>> _______________________________________________
>> Scikit-learn-general mailing list
>> [email protected]
>> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>>
>>
>
>
> ------------------------------------------------------------------------------
> Learn Windows Azure Live! Tuesday, Dec 13, 2011
> Microsoft is holding a special Learn Windows Azure training event for
> developers. It will provide a great way to learn Windows Azure and what it
> provides. You can attend the event by watching it streamed LIVE online.
> Learn more at http://p.sf.net/sfu/ms-windowsazure
> _______________________________________________
> Scikit-learn-general mailing list
> [email protected]
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>
>
--
Best Wishes
--------------------------------------------
Meng Xinfan（蒙新泛）
Institute of Computational Linguistics
Department of Computer Science & Technology
School of Electronic Engineering & Computer Science
Peking University
Beijing, 100871
China
------------------------------------------------------------------------------
Learn Windows Azure Live! Tuesday, Dec 13, 2011
Microsoft is holding a special Learn Windows Azure training event for
developers. It will provide a great way to learn Windows Azure and what it
provides. You can attend the event by watching it streamed LIVE online.
Learn more at http://p.sf.net/sfu/ms-windowsazure
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