[scikit-learn] Random Forest Regressor -- Implementation in C++

[Chidhambaranathan R]

Hi all,

I'm using sklearn Randon Forest Regressor. I have trained the model in
Python and dumped the model using Pickle. The model is used inside C++
application for prediction. Currently I have implemented predict function
using "Embedding Python in C++" concept. However, the problem is, it is
causing huge runtime overhead and I can't afford that much runtime.

Is there a way, can I extract the decision tree information and RF
parameters from RF trained model? I can implemented the decision trees with
RF parameters in C++.

If you aware of alternative directions, please let me know.
I would appreciate it. Thanks.

-- 
Regards,
Chidham
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