Re: [scikit-learn] Compiled trees

, Maciek Wójcikowski [email protected] 2016-08-11 23:39 GMT+02:00 Ali Zude via scikit-learn : 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 "Multiproce

[scikit-learn] Compiled trees

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

Re: [scikit-learn] Speeding up RF regressors

ly) 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 : 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

[scikit-learn] Speeding up RF regressors

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? -