Name
Abstract | ||
|---|---|---|
•A novel twin support vector machine method is presented.•A robust optimization scheme is used to derive second-order cone programming models.•The proposal extends the nonparallel support vector machine approach.•Best performance is achieved in experiments on benchmark datasets. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.neucom.2019.07.072 | Neurocomputing |
Keywords | Field | DocType |
Support vector machines,Twin support vector machines,Nonparallel support vector machines,Second-order cone programming,Robustness | Second-order cone programming,Binary classification,Pattern recognition,Support vector machine,Algorithm,Robustness (computer science),Artificial intelligence,Quadratic programming,Hyperplane,Mathematics,Probabilistic framework | Journal |
Volume | ISSN | Citations |
364 | 0925-2312 | 1 |
PageRank | References | Authors |
0.35 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julio López | 1 | 124 | 13.49 |
| Sebastián Maldonado | 2 | 508 | 32.45 |
| Miguel Carrasco | 3 | 21 | 4.35 |