[scikit-learn] Compiled trees

[Ali Zude]

sklearn-compiledtrees==1.3


      Von: Maciek Wójcikowski <maciek at wojcikowski.pl>
 An: Ali Zude <zude07 at yahoo.com>; Scikit-learn user and developer mailing list <scikit-learn at python.org> 
 Gesendet: 7:30 Freitag, 12.August 2016
 Betreff: Re: [scikit-learn] Compiled trees
   
Which version of compiledtrees are you using?
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Pozdrawiam,  |  Best regards,
Maciek Wójcikowski
maciek at wojcikowski.pl

2016-08-11 23:39 GMT+02:00 Ali Zude via scikit-learn <scikit-learn at python.org>:

Dear All,
I am trying to speed up the prediction of Random Forests. I've used compiledtress, which was useful, but since I have 6 models and once I've loaded all of them I got "Multiprocessing exception:" 

here is my models in the code:
...model1=joblib.load('/models/ model1.pkl'') model2=joblib.load('/models/ model2.pkl') model3=joblib.load('/models/ model3.pkl') model4=compiledtrees. CompiledRegressionPredictor( joblib.load('/models/model4. pkl')) model5=compiledtrees. CompiledRegressionPredictor( joblib.load('/models/model4. pkl')) model6=compiledtrees. CompiledRegressionPredictor( joblib.load('/models/model4. pkl')) 
model1=compiledtrees. CompiledRegressionPredictor( model1) model2=compiledtrees. CompiledRegressionPredictor( model2) model3=compiledtrees. CompiledRegressionPredictor( model3)....
Now I'm trying to use MultiOutputRegressor( RandomForestRegressor()), however, I could not find any tool to do model selection, can anyone help me either to solve the first problem or the second one
Best regards

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