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A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification Problems

Overview of attention for article published in Machine Learning, November 2001
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#31 of 1,266)
  • High Attention Score compared to outputs of the same age (96th percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
3 X users
wikipedia
3 Wikipedia pages
googleplus
1 Google+ user
linkedin
1 LinkedIn user
q&a
2 Q&A threads

Citations

dimensions_citation
1623 Dimensions

Readers on

mendeley
1263 Mendeley
citeulike
7 CiteULike
Title
A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification Problems
Published in
Machine Learning, November 2001
DOI 10.1023/a:1010920819831
Authors

David J. Hand, Robert J. Till

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,263 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 21 2%
United Kingdom 10 <1%
Germany 9 <1%
Brazil 5 <1%
Spain 4 <1%
Belgium 4 <1%
Australia 3 <1%
Portugal 3 <1%
Denmark 3 <1%
Other 29 2%
Unknown 1172 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 280 22%
Researcher 202 16%
Student > Master 188 15%
Student > Bachelor 89 7%
Student > Doctoral Student 60 5%
Other 206 16%
Unknown 238 19%
Readers by discipline Count As %
Computer Science 322 25%
Engineering 157 12%
Agricultural and Biological Sciences 97 8%
Mathematics 57 5%
Medicine and Dentistry 49 4%
Other 276 22%
Unknown 305 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 31 October 2023.
All research outputs
#1,480,208
of 26,017,215 outputs
Outputs from Machine Learning
#31
of 1,266 outputs
Outputs of similar age
#1,095
of 47,571 outputs
Outputs of similar age from Machine Learning
#2
of 3 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,266 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 97% 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 47,571 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 96% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.