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MATLAB toolbox for the algorithm IKSVM-DC.

Copyright: 
Hai-Ming Xu1 (heimingx@seu.edu.cn), Hui Xue1 (hxue@seu.edu.cn),
Xiao-Hong Chen2 (lyandcxh@nuaa.edu.cn), Yun-Yun Wang3 (wangyunyun@njupt.edu.cn)
1School of Computer Science and Engineering, Southeast University, Nanjing 210096, P.R.China
2College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China
3School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, 210046, China
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0. Contents
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0. Contents
1. Introduction
2. Requirements
3. Installation
4. How to start?

1.Introduction
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This package implements a novel indefinite kernel SVM algorithm named IKSVM-DC.
The algorithm IKSVM-DC is specially designed for the primal form of indefinite 
kernel SVM problem. Further details about IKSVM-DC can be found in the following papers:

H.-M. Xu, H. Xue, X.-H. Chen, Y.-Y. Wang. Solving Indefinite Kernel Support Vector Machine
with Difference of Convex Functions Programming. In: Proceedings of the 31th AAAI Conference 
on Artificial Intelligence (AAAI'17), San Francisco, California USA, in press.

This package can be used freely for academic, non-profit purposes. 
If you intend to use it for commercial development, please contact us. 
Please feel free to contact us if you find anything wrong 
or you have any further questions.

2. Requirements
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- Matlab, version 2014a and higher.
- The package is mostly self-contain. 
Several functions require the Optimization Toolbox, e.g., CVX toolbox or Mosek toolbox.

3. Installation
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- Create a directory of your choice and copy the toolbox there.
- Set the path in your Matlab to add the directory you just created.

4. How to start?
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To help you start working with indefinite kernel SVM, we provide a demo(See demo.m) in this package. 
You can follow the procedure as described in the demo.

Please read and play with the demo to get started.
