| Title: | Multi-class classification SVM methods |
| Authors: | Zhao Di |
| Keywords: | материалы конференций;Support Vector Machine;multi-classification |
| Issue Date: | 2022 |
| Publisher: | БГУИР |
| Citation: | Zhao Di. Multi-class classification SVM methods / Zhao Di // Технологии передачи и обработки информации : материалы международного научно-технического семинара, Минск, март-апрель 2022 г. / Белорусский государственный университет информатики и радиоэлектроники. – Минск, 2022. – С. 85–87. |
| Abstract: | Support Vector Machine (SVM) was first proposed by Cortes and Vapnik in 1995. It is developed from the linear separable classification problem. The basic principle of SVM is to use a hyperplane to divide data into two categories, but in many classification problems, the sample is not linear, and the classification problem is multi-classification. We need to solve the multiclassification problem on a dichotomy basis. |
| URI: | https://libeldoc.bsuir.by/handle/123456789/46942 |
| Appears in Collections: | Технологии передачи и обработки информации : материалы международного научно-технического семинара (2022)
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