[scikit-learn] Speeding up RF regressors

[Maciek Wójcikowski]

Hi Ali,

I'm using sklearn-compiledtrees [
https://github.com/ajtulloch/sklearn-compiledtrees] on quite large trees
(pickle size ~1GB, compiled ~100MB) and the speedup is gigantic (never
measured it properly) but I'd say it's over 10x.

----
Pozdrawiam,  |  Best regards,
Maciek Wójcikowski
maciek at wojcikowski.pl

2016-08-11 13:21 GMT+02:00 Ali Zude via scikit-learn <
scikit-learn at python.org>:

> Hi all,
>
> I've 6 RF models and I am using them online to predict 6 different
> variables (using the same features), models quality (error in test data is
> good). However, the online prediction is very very slow.
> How can I speed up the prediction?
>
>    -     Can I import models into C++ code?
>    -     Is it useful to upgrade to scikit-learn 0.18? and then use
>    multi-output models?
>    -     Is sklearn-compiledtreesuseful, they are claiming that it will
>    speed the prediction (5x-8x)times?
>       - I could not use because of array2d error >>PyPi
>
> Thank you for your help
>
> Regards
> Ali
>
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