Can anyone help with Random Decision Forest implementation in C++?

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Luca Pinello

Take a look here: http://blog.yhathq.com/posts/random-forests-in-python.html

The package sklearn (python) is well maintained and easy to understand and edit.

Branko Samarzija

Random forests have been implemented as a part of the OpenCV library. Here is a link to the documentation pages: http://docs.opencv.org/modules/ml/doc/random_trees.html?highlight=forest

The OpenCV library is a C/C++ library (Python is also supported) and it contains lots of algorithms and data structures related to computer vision and machine learning. You can get it here: http://opencv.org/downloads.html

The sources are available from the Git repository:

https://github.com/Itseez/opencv

Look in the opencv/samples directory (for example, opencv/samples/c/tree_engine.cpp)

If you are not familiar with the library, the best way to start is to go through the tutorials: http://docs.opencv.org/doc/tutorials/tutorials.html

It takes a little time to get used to it, but the library is really helpful and it's worth to give it a try.

Thales Sehn Körting

Dear,

please check this youtube video, where I explain how Random Forest algorithm works

http://youtu.be/loNcrMjYh64

Regards

Gerard Sanroma

There is also the RF code of criminisi's book which is in c++ and is intended for didactic purposes so it shoul be easy to tweak.

http://research.microsoft.com/apps/mobile/showpage.aspx?page=/en-us/projects/decisionforests/

David Vázquez

I strongly recommend the criminisi implementation. It is very easy to understand. I have implemented several split functions for this code. If you need any help with this I can help you. We have implemented a paper of random forest where we changed the split function by a SVM:

Javier Marin, David Vazquez, Antonio Lopez, Jaume Amores, & Bastian Leibe. (2013). "Random Forests of Local Experts for Pedestrian Detection " In International Conference on Computer Vision.