Please remove me as well.

On Thursday, August 11, 2016, o m <[email protected]> wrote:

> Can someone please take me off this list? Thanks
>
> Sent from my iPhone
>
> On Aug 11, 2016, at 9:10 AM, Maciek Wójcikowski <[email protected]
> <javascript:_e(%7B%7D,'cvml','[email protected]');>> wrote:
>
> First of all the pypi version is outdated, please install using
>>
>> pip install git+https://github.com/ajtulloch/sklearn-compiledtrees.git
>
>
> Secondly, which scikit-learn version are you using?
>
> ----
> Pozdrawiam,  |  Best regards,
> Maciek Wójcikowski
> [email protected]
> <javascript:_e(%7B%7D,'cvml','[email protected]');>
>
> 2016-08-11 13:31 GMT+02:00 Ali Zude <[email protected]
> <javascript:_e(%7B%7D,'cvml','[email protected]');>>:
>
>> Thnx Maciek,
>>
>> I've tried to use it but I could not sort out the PyPi problem,  see the
>> error below. Thanks in advance.
>>
>> ---> 16 import compiledtrees
>> /home/ali/anaconda2/lib/python2.7/site-packages/compiledtrees/__init__.py in 
>> <module>()----> 1 from compiledtrees.compiled import 
>> CompiledRegressionPredictor      2       3 __all__ = 
>> ["CompiledRegressionPredictor"]
>> /home/ali/anaconda2/lib/python2.7/site-packages/compiledtrees/compiled.py in 
>> <module>()      1 from __future__ import print_function      2 ----> 3 from 
>> sklearn.utils import array2d      4 from sklearn.tree.tree import 
>> DecisionTreeRegressor, DTYPE      5 from sklearn.ensemble.gradient_boosting 
>> import GradientBoostingRegressor
>> ImportError: cannot import name array2d
>>
>>
>> Kind regards
>> Ali
>>
>> ------------------------------
>> *Von:* Maciek Wójcikowski <[email protected]
>> <javascript:_e(%7B%7D,'cvml','[email protected]');>>
>> *An:* Ali Zude <[email protected]
>> <javascript:_e(%7B%7D,'cvml','[email protected]');>>; Scikit-learn user
>> and developer mailing list <[email protected]
>> <javascript:_e(%7B%7D,'cvml','[email protected]');>>
>> *Gesendet:* 12:26 Donnerstag, 11.August 2016
>> *Betreff:* Re: [scikit-learn] Speeding up RF regressors
>>
>> 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
>> [email protected]
>> <javascript:_e(%7B%7D,'cvml','[email protected]');>
>>
>> 2016-08-11 13:21 GMT+02:00 Ali Zude via scikit-learn <
>> [email protected]
>> <javascript:_e(%7B%7D,'cvml','[email protected]');>>:
>>
>> 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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>>
>>
>>
>>
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