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Mendeley readers
| Chapter title |
Multi-label Learning
|
|---|---|
| Chapter number | 7 |
| Book title |
Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods
|
| Published by |
Springer, Cham, January 2019
|
| DOI | 10.1007/978-3-030-04663-7_7 |
| Book ISBNs |
978-3-03-004662-0, 978-3-03-004663-7
|
| Authors |
Sarah Vluymans |
Mendeley readers
The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 91 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 19 | 21% |
| Student > Master | 11 | 12% |
| Student > Bachelor | 10 | 11% |
| Researcher | 7 | 8% |
| Student > Doctoral Student | 3 | 3% |
| Other | 11 | 12% |
| Unknown | 30 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 43 | 47% |
| Engineering | 7 | 8% |
| Mathematics | 2 | 2% |
| Economics, Econometrics and Finance | 2 | 2% |
| Business, Management and Accounting | 1 | 1% |
| Other | 2 | 2% |
| Unknown | 34 | 37% |