Sample Reduction for Support Vector Data Description (SVDD) by Farthest Boundary Point Estimation (FBPE) using Gradients of Data Density

Author:

Pareek Pratyush1,Bhardwaj Aaryan1,Patro Sanskar1,Arora Anirudh1,Kaur Maini Muskan Deep1,Kumar Bagesh1,Vyas O. P.1

Affiliation:

1. Indian Institute of Information Technology Allahabad, India

Publisher

ACM

Reference31 articles.

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2. Cueing, feature discovery, and one-class learning for synthetic aperture radar automatic target recognition

3. [3]GeeksForGeeks (2022 Jan 04). Parzen Windows density estimation technique. GeeksForGeeks. https://www.geeksforgeeks.org/parzen-windows-density-estimation-technique/ [3]GeeksForGeeks (2022 Jan 04). Parzen Windows density estimation technique. GeeksForGeeks. https://www.geeksforgeeks.org/parzen-windows-density-estimation-technique/

4. A Random Forest Based Approach for One Class Classification in Medical Imaging

5. [ 5 ] Schölkopf , B. , Williamson , R. C. , Smola , A. , Shawe-Taylor , J. , & Platt , J. ( 1999 ). Support vector method for novelty detection. Advances in neural information processing systems, 12 . [5] Schölkopf, B., Williamson, R. C., Smola, A., Shawe-Taylor, J., & Platt, J. (1999). Support vector method for novelty detection. Advances in neural information processing systems, 12.

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