Name
Title | ||
|---|---|---|
An Improved SVM Based on 1-Norm for Selection of Personal Credit Scoring Index System |
Abstract | ||
|---|---|---|
The selection of evaluating index system is the key to personal credit scoring, which is a feature selection problem.By improving the typical SVM based on 1-norm, which can select the important and necessary feature of samples, an improved SVM based on 1-norm adapted to the selection of personal credit scoring index system is proposed. Experimental results shows that the new improved method can select evaluating index system with small scale and enhance the generality ability and reduce the arithmetic complexity of the classification machine. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72395-0_56 | ISNN (3) |
Keywords | Field | DocType |
improved svm,personal credit,typical svm,feature selection problem,new improved method,necessary feature,personal credit scoring index,index system,arithmetic complexity,personal credit scoring,classification machine,indexation,feature selection | Data mining,Feature selection,Pattern recognition,Computer science,Support vector machine,Norm (social),Index system,Artificial intelligence,Generality,Machine learning | Conference |
Volume | ISSN | Citations |
4493 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Xue | 1 | 4 | 2.31 |
| Guoping He | 2 | 91 | 13.59 |