First of all the pypi version is outdated, please install using 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] 2016-08-11 13:31 GMT+02:00 Ali Zude <[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]> > *An:* Ali Zude <[email protected]>; Scikit-learn user and developer > mailing list <[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] > > 2016-08-11 13:21 GMT+02:00 Ali Zude via scikit-learn < > [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 > > ______________________________ _________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/ mailman/listinfo/scikit-learn > <https://mail.python.org/mailman/listinfo/scikit-learn> > > > > >
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