sklearn-compiledtrees==1.3
Von: Maciek Wójcikowski <[email protected]>
An: Ali Zude <[email protected]>; Scikit-learn user and developer mailing list
<[email protected]>
Gesendet: 7:30 Freitag, 12.August 2016
Betreff: Re: [scikit-learn] Compiled trees
Which version of compiledtrees are you using?
----
Pozdrawiam, | Best regards,
Maciek Wójcikowski
[email protected]
2016-08-11 23:39 GMT+02:00 Ali Zude via scikit-learn <[email protected]>:
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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