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Reduction Techniques for Instance-Based Learning Algorithms

Overview of attention for article published in Machine Learning, March 2000
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)

Mentioned by

patent
2 patents

Citations

dimensions_citation
946 Dimensions

Readers on

mendeley
318 Mendeley
citeulike
3 CiteULike
Title
Reduction Techniques for Instance-Based Learning Algorithms
Published in
Machine Learning, March 2000
DOI 10.1023/a:1007626913721
Authors

D. Randall Wilson, Tony R. Martinez

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 318 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
Colombia 3 <1%
Spain 3 <1%
Italy 3 <1%
Germany 2 <1%
Turkey 2 <1%
France 2 <1%
Korea, Republic of 1 <1%
Cuba 1 <1%
Other 10 3%
Unknown 286 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 92 29%
Student > Master 61 19%
Researcher 31 10%
Professor > Associate Professor 21 7%
Student > Doctoral Student 18 6%
Other 48 15%
Unknown 47 15%
Readers by discipline Count As %
Computer Science 175 55%
Engineering 40 13%
Mathematics 6 2%
Business, Management and Accounting 5 2%
Agricultural and Biological Sciences 5 2%
Other 23 7%
Unknown 64 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 17 May 2022.
All research outputs
#5,446,994
of 25,374,647 outputs
Outputs from Machine Learning
#162
of 1,225 outputs
Outputs of similar age
#6,659
of 41,738 outputs
Outputs of similar age from Machine Learning
#2
of 2 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,225 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done well, scoring higher than 83% 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 41,738 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.