| Title |
On label dependence and loss minimization in multi-label classification
|
|---|---|
| Published in |
Machine Learning, June 2012
|
| DOI | 10.1007/s10994-012-5285-8 |
| Authors |
Krzysztof Dembczyński, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 180 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 1% |
| United Kingdom | 1 | <1% |
| Belgium | 1 | <1% |
| Spain | 1 | <1% |
| United States | 1 | <1% |
| Poland | 1 | <1% |
| Unknown | 173 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 49 | 27% |
| Student > Master | 32 | 18% |
| Student > Doctoral Student | 18 | 10% |
| Researcher | 17 | 9% |
| Student > Bachelor | 13 | 7% |
| Other | 22 | 12% |
| Unknown | 29 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 105 | 58% |
| Engineering | 16 | 9% |
| Mathematics | 6 | 3% |
| Agricultural and Biological Sciences | 3 | 2% |
| Business, Management and Accounting | 3 | 2% |
| Other | 11 | 6% |
| Unknown | 36 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 July 2012.
All research outputs
#15,247,248
of 22,671,366 outputs
Outputs from Machine Learning
#674
of 951 outputs
Outputs of similar age
#106,311
of 166,795 outputs
Outputs of similar age from Machine Learning
#6
of 10 outputs
Altmetric has tracked 22,671,366 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 951 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 166,795 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.