Decision Tree and Decision Forest

Version (5.57 MB) by Quan Wang
This software implements decision tree/forest classifier in C++/MEX.


Updated 10 Mar 2014

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This package implements the decision tree and decision forest techniques in C++, and can be compiled with MEX and called by MATLAB. The algorithm is highly efficient, and has been used in these papers:

[1] Quan Wang, Yan Ou, A. Agung Julius, Kim L. Boyer and Min Jun Kim, "Tracking Tetrahymena Pyriformis Cells using Decision Trees", 2012 21st International Conference on Pattern Recognition (ICPR), Pages 1843-1847, 11-15 Nov. 2012.

[2] Quan Wang, Dijia Wu, Le Lu, Meizhu Liu, Kim L. Boyer, and Shaohua Kevin Zhou, "Semantic Context Forests for Learning-Based Knee Cartilage Segmentation in 3D MR Images", MICCAI 2013: Workshop on Medical Computer Vision.

Cite As

Quan Wang (2023). Decision Tree and Decision Forest (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2012b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

Changed the positions of several delete[] commands to optimize memory use.

Added decision forest functionalities.

Better encapsulation of the HashTable class.

Optimized the memory use of getEntropyDecrease() function.

Rewrite the code in C++/MEX. Generate to multi-class.