Name
Abstract | ||
|---|---|---|
In this paper we use Kohonen's Self-Organizing Map (SOM) for surveying the financial status of Spanish companies. From it, we infer which are the most relevant variables, so that a fast diagnostic on their status can be reached and, besides, explained via a few rules of thumb extracted from the behavior of those variables. This map can be used as part of a decision making process, or as a first stage in an automatic classification tool. Results show that variables, identified in an easy and visual way (using SOM and U-Matrix graph), are in agreement with those obtained using parametric and non-parametric tests, which are more complex and difficult to apply. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-73007-1_93 | IWANN |
Keywords | Field | DocType |
u-matrix graph,financial status,self-organizing map,automatic classification tool,spanish company,financial distress,relevant variable,non-parametric test,case study,decision making process,rule of thumb | Data mining,Graph,Computer science,Self-organizing map,Bankruptcy prediction,Parametric statistics,Rule of thumb,Artificial intelligence,Business failure,Decision-making,Financial distress,Machine learning | Conference |
Volume | ISSN | Citations |
4507 | 0302-9743 | 3 |
PageRank | References | Authors |
0.41 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. M. Mora | 1 | 99 | 10.00 |
| J. L. Laredo | 2 | 69 | 5.89 |
| P. A. Castillo | 3 | 134 | 13.95 |
| J. J. Merelo | 4 | 363 | 33.51 |