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Mendeley readers
| Title |
Credit Scoring: A Review on Support Vector Machines and Metaheuristic Approaches
|
|---|---|
| Published in |
Advances in Operations Research, March 2019
|
| DOI | 10.1155/2019/1974794 |
| Authors |
R. Y. Goh, L. S. Lee |
Mendeley readers
The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 94 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 10% |
| Student > Ph. D. Student | 8 | 9% |
| Lecturer | 5 | 5% |
| Student > Bachelor | 4 | 4% |
| Researcher | 4 | 4% |
| Other | 15 | 16% |
| Unknown | 49 | 52% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 17 | 18% |
| Business, Management and Accounting | 10 | 11% |
| Engineering | 5 | 5% |
| Mathematics | 3 | 3% |
| Economics, Econometrics and Finance | 3 | 3% |
| Other | 6 | 6% |
| Unknown | 50 | 53% |