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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