IMAGE SETS RECOGNITION USING POLYHEDRAL CONIC CLASSIFIERS
This is a toolbox that implements SVM based Binary Hierarchical Decision Trees (BHDTs). In order to use this toolbox, you must first download the svm toolbox from http://asi.insa-rouen.fr/enseignants/~arakotom/toolbox/index.html. All programs are written in Matlab, and you can also find DAG SVM implementation in the package as well. You should first read the paper titled New clustering algorithms for the support vector machine based hierarchical classification (Pattern Recognition Letters, 2010) by Hakan Cevikalp to become familiar with the algorithms.
- Download the SVM toolbox from the web address given above.
- Add the SVM toolbox directory and all sub-directories in the Matlab path.
- Download BHDTs.zip files and uncompress them in an appropriate directory.
- Add the toolbox directory in the Matlab path.
- Launch the demo.m program in order to verify if the toolbox works properly, the program takes only a few minutes to finish. (you can also repeat the experiments described in Cevikalp s paper by running Demo_paper_XOR.m and Demo_Coil.m programs if you have time -- they take a few hours)
- Please read the function descriptions and explanations in demo programs in order to learn their usage. Please cite the paper paper titled New clustering algorithms for the support vector machine based hierarchical classification (Pattern Recognition Letters, 2010) by Hakan Cevikalp if you used this toolbox.
If you find a bug, please send an email to email@example.com