Name
Abstract | ||
|---|---|---|
A new SVM model used to calculate the optimal value of cost parameter C for particular problems of linearity non-separability of data is presented in this paper. The new SVM model is formulated in the form of one of MPEC problems with an integer objective function. A lower bound, positive number, C"0 is required to provide for avoiding choosing a candidate set of C. Numerical experiments show that this model for choice of C is suitable for solving SVM problems. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.eswa.2007.01.004 | Expert Syst. Appl. |
Keywords | Field | DocType |
support vector machine,optimal value,data mining,cost parameter c,cost parameter,c. numerical experiment,two-level approach,positive number,particular problem,integer objective function,linearity non-separability,new svm model,mpec problem,nonlinear programming,svm problem,lower bound,objective function | Integer,Data mining,Mathematical optimization,Upper and lower bounds,Computer science,Nonlinear programming,Linearity,Support vector machine,Artificial intelligence,Machine learning | Journal |
Volume | Issue | ISSN |
34 | 2 | Expert Systems With Applications |
Citations | PageRank | References |
1 | 0.43 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yulin Dong | 1 | 29 | 2.53 |
| Zhonghang Xia | 2 | 120 | 17.28 |
| Zun-Quan Xia | 3 | 249 | 15.85 |