Name
Abstract | ||
|---|---|---|
This article presents a method joining Support Vector Machines (SVM), genetic search and multivariate analysis for identification of bankrupt companies. This study proposed to join widely used Altman Z-Score with Support Vector Machines to create a classifier that might be used to evaluate and forecast possible bankrupt companies. A genetic search algorithm is employed for relevant attribute selection to reduce the dimensionality of data. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15402-7_3 | Lecture Notes in Business Information Processing |
Keywords | Field | DocType |
Support Vector Machines,SVM,artificial intelligence,machine learning,credit risk,evaluation,bankruptcy,Altman | Structured support vector machine,Data mining,Feature selection,Computer science,Support vector machine,Curse of dimensionality,Genetic search,Artificial intelligence,Multivariate analysis,Classifier (linguistics),Machine learning,Credit risk | Conference |
Volume | ISSN | ISBN |
57 | 1865-1348 | 978-3-642-15401-0 |
Citations | PageRank | References |
3 | 0.41 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paulius Danenas | 1 | 35 | 5.07 |
| Gintautas Garsva | 2 | 41 | 4.95 |