Name
Abstract | ||
|---|---|---|
The analysis and management of business failure has been recognized to be important in the area of financial management in the evaluation of firms' performance and the assessment of their viability. To this end, effective failure-prediction models are needed. This paper describes a new approach to prediction of business failure using the total margin algorithm which is a kind of support vector machine. It will be shown that the proposed method can evaluate the risk of failure better than existing methods through some real data. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-30132-5_63 | LECTURE NOTES IN ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
financial management,support vector machine | Data mining,Industrial engineering,Computer science,Support vector machine,Business failure,Financial management | Conference |
Volume | ISSN | Citations |
3213 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yeboon Yun | 1 | 38 | 8.60 |
| Min Yoon | 2 | 34 | 10.38 |
| Hirotaka Nakayama | 3 | 122 | 23.18 |
| Wataru Shiraki | 4 | 1 | 2.69 |