[scikit-learn] How to dump a model to txt file?

[Roman Yurchak]

Also, there is an effort on converting trained scikit-learn models to 
other languages (e.g. C) in https://github.com/nok/sklearn-porter
but it does not support GradientBoostingRegressor (yet).

On 13/04/17 23:27, federico vaggi wrote:
> If you want to use the model from C++ code, the easiest way is to
> probably use Boost/Python
> (http://www.boost.org/doc/libs/1_62_0/libs/python/doc/html/index.html).
> Alternatively, use another gradient boosting library that has a C++ API
> (like XGBoost).
>
> Keep in mind, if you want to call Python code from C++ you will have to
> bundle a Python interpreter as well as all the dependencies.
>
> On Thu, 13 Apr 2017 at 14:23 Sebastian Raschka <se.raschka at gmail.com
> <mailto:se.raschka at gmail.com>> wrote:
>
>     Hi,
>
>     not sure how this could generally work. However, you could at least
>     dump the model parameters for e.g., linear models and compute the
>     prediction via
>
>     w_1 * x1 + w_2 * x_2 + … + w_n * x_n + bias
>
>     over the n features.
>
>     To write various model attributes to text files, you could use json,
>     e.g., see https://cmry.github.io/notes/serialize
>     However, I don’t think that this approach will solve the problem of
>     loading the model into C++.
>
>     Best,
>     Sebastian
>
>     > On Apr 13, 2017, at 4:58 PM, 老陈 <26743610 at qq.com
>     <mailto:26743610 at qq.com>> wrote:
>     >
>     > Hi,
>     >
>     > I am working on GradientBoostingRegressor these days and I am
>     wondering if there is a way to dump the model into txt file, or any
>     other format that can be processed by c++
>     >
>     > My production system is in c++, so I want use the python-trained
>     tree model in c++ for production.
>     >
>     > Has anyone ever done this before?
>     >
>     > thanks
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