cuicui1989 / deep-kernel-learning-for-one-class-classification

Minimum Variance-Embedded Deep Kernel Regularized Least Square Method for One-class Classification and Its Applications to Biomedical Data

Minimum Variance-Embedded Deep Kernel Learning for One-class Classification (DKRLVOC)

Paper: Minimum Variance-Embedded Deep Kernel Regularized Least Square Method for One-class Classification and Its Applications to Biomedical Data (Submitted)

Authors: Chandan Gautam, Pratik K Mishra, Aruna Tiwari, Bharat Richhariya, Hari Mohan Pandey, Shuihua Wang, M. Tanveer

For execution, simply go to the one of the demo folders ('Demo_Alzheimer', 'Demo_mediumDatasets', or 'Demo_smallDatasets'), and open '.m' file in MATLAB and execute that. All source codes and datases are available in 'src' folder.

This repository also contains implementation of the following papers for comparison:

1. OCKELM

# Leng, Q., Qi, H., Miao, J., Zhu, W., & Su, G. (2015). One-class classification with extreme learning machine. Mathematical problems in engineering, 2015.

2. VOCKELM

# Mygdalis, V., Iosifidis, A., Tefas, A., & Pitas, I. (2016, September). One class classification applied in facial image analysis. In 2016 IEEE International Conference on Image Processing (ICIP) (pp. 1644-1648). IEEE.

3. ML-OCKELM

# Dai, H., Cao, J., Wang, T., Deng, M., & Yang, Z. (2019). Multilayer one-class extreme learning machine. Neural Networks, 115, 11-22.

For any query related to the above code, you can reach me at [email protected]