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 > >
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