Name
Abstract | ||
|---|---|---|
Fisher-regularized support vector machine (Fish-erSVM) can approximatively fulfill the Fisher criterion and obtain good statistical separability, which is a combined method of the support vector machine and Fisher discriminant analysis. However, the hinge loss function is related to the shortest distance between two-class sets, and FisherSVM may be hence sensitive to noise. To remedy it, the pinba... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IJCNN52387.2021.9533502 | 2021 International Joint Conference on Neural Networks (IJCNN) |
Keywords | DocType | ISSN |
Support vector machines,Neural networks,Interference,Fasteners,Pins,Quadratic programming,Computational complexity | Conference | 2161-4393 |
ISBN | Citations | PageRank |
978-1-6654-3900-8 | 0 | 0.34 |
References | Authors | |
14 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhengqi Zhang | 1 | 0 | 0.34 |
| Li Zhang | 2 | 363 | 39.03 |
| Zhao Zhang | 3 | 938 | 65.99 |