| Title |
Measuring classifier performance: a coherent alternative to the area under the ROC curve
|
|---|---|
| Published in |
Machine Learning, June 2009
|
| DOI | 10.1007/s10994-009-5119-5 |
| Authors |
David J. Hand |
X Demographics
The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 13% |
| Finland | 2 | 9% |
| India | 2 | 9% |
| United States | 1 | 4% |
| Sweden | 1 | 4% |
| Germany | 1 | 4% |
| Puerto Rico | 1 | 4% |
| Australia | 1 | 4% |
| Unknown | 11 | 48% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 17 | 74% |
| Practitioners (doctors, other healthcare professionals) | 3 | 13% |
| Scientists | 3 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 911 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 19 | 2% |
| United Kingdom | 12 | 1% |
| Germany | 7 | <1% |
| Canada | 6 | <1% |
| Switzerland | 5 | <1% |
| Australia | 4 | <1% |
| Brazil | 4 | <1% |
| Belgium | 4 | <1% |
| Sweden | 3 | <1% |
| Other | 26 | 3% |
| Unknown | 821 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 212 | 23% |
| Researcher | 163 | 18% |
| Student > Master | 150 | 16% |
| Student > Bachelor | 50 | 5% |
| Professor > Associate Professor | 43 | 5% |
| Other | 165 | 18% |
| Unknown | 128 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 276 | 30% |
| Engineering | 76 | 8% |
| Agricultural and Biological Sciences | 67 | 7% |
| Mathematics | 64 | 7% |
| Medicine and Dentistry | 43 | 5% |
| Other | 212 | 23% |
| Unknown | 173 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 38. 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 13 January 2024.
All research outputs
#1,108,965
of 25,904,557 outputs
Outputs from Machine Learning
#17
of 1,271 outputs
Outputs of similar age
#2,814
of 117,064 outputs
Outputs of similar age from Machine Learning
#1
of 5 outputs
Altmetric has tracked 25,904,557 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,271 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 98% of its peers.
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 117,064 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them