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Localized Multiple Kernel Learning for Anomaly Detection: One-Class Classification

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Paper

C. Gautam, R. Balaji, K. Sudharsan, A. Tiwari, and K. Ahuja, Localized Multiple Kernel Learning for Anomaly Detection: One-Class Classification, Knowledge-Based Systems, vol. 165, pp. 241-252, 2018 (ELSEVIER).

              https://www.sciencedirect.com/science/article/pii/S0950705118305823

Follow the following steps to replicate the results:

  1. To execute the above codes, simply open the above codes in MATLAB and run Main.m file. This code will generate results for Gaussian-Polynomial-Polynomial and Gaussian-Polynomial-Linear combination using linear sigmoid gating function for LMKAD. By changing the parameters, you can obtain the results for other combination of kernel and gating function.

  2. After executing the 'Main.m' file, two files, namely 'gpp_lsoft.mat' and 'gpl_lsoft.mat'.

  3. Then execute 'Extract_all_results.m' file. It will yield results of all mentioned datasets in the paper in the MATLAB workspace.

After following above three steps, you should get exact results as mentioned in paper.

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

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