Name
Abstract | ||
|---|---|---|
•Support Vector Data Description (SVDD) is a popular kernel-based unsupervised one-class classification method. The Gaussian kernel is the most common used kernel.•The Gaussian kernel has a tuning parameter, the kernel bandwidth, and it is important to choose it correctly.•We propose an automated, unsupervised, bandwidth selection method for SVDD.•Our proposed bandwidth is also appropriate for selecting the bandwidth for One Class Support Vector Machines (OCSVM). |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.patcog.2020.107662 | Pattern Recognition |
Keywords | DocType | Volume |
Support vector data description,SVDD,One-class support vector machines,OCSVM,Gaussian kernel,Automatic tuning,Gaussian kernel bandwidth | Journal | 111 |
Issue | ISSN | Citations |
1 | 0031-3203 | 0 |
PageRank | References | Authors |
0.34 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Chaudhuri | 1 | 11 | 5.82 |
| Carol Sadek | 2 | 1 | 1.02 |
| D. Kakde | 3 | 10 | 4.80 |
| Haoyu Wang | 4 | 0 | 1.69 |
| Wenhao Hu | 5 | 0 | 1.35 |
| Hansi Jiang | 6 | 0 | 0.34 |
| Seunghyun Kong | 7 | 8 | 2.35 |
| Yuewei Liao | 8 | 0 | 0.34 |
| Sergiy Peredriy | 9 | 2 | 2.27 |