| Title |
Using meta-learning for automated algorithms selection and configuration: an experimental framework for industrial big data
|
|---|---|
| Published in |
Journal of Big Data, April 2022
|
| DOI | 10.1186/s40537-022-00612-4 |
| Authors |
Moncef Garouani, Adeel Ahmad, Mourad Bouneffa, Mohamed Hamlich, Gregory Bourguin, Arnaud Lewandowski |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 65 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 9% |
| Unspecified | 4 | 6% |
| Student > Postgraduate | 3 | 5% |
| Student > Bachelor | 3 | 5% |
| Student > Master | 3 | 5% |
| Other | 10 | 15% |
| Unknown | 36 | 55% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 11 | 17% |
| Computer Science | 10 | 15% |
| Unspecified | 4 | 6% |
| Agricultural and Biological Sciences | 2 | 3% |
| Environmental Science | 1 | 2% |
| Other | 4 | 6% |
| Unknown | 33 | 51% |