[scikit-learn] Compiled trees

[Ali Zude]

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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