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Benchmarking Least Squares Support Vector Machine Classifiers

Overview of attention for article published in Machine Learning, January 2004
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Mentioned by

patent
2 patents

Citations

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583 Dimensions

Readers on

mendeley
197 Mendeley
Title
Benchmarking Least Squares Support Vector Machine Classifiers
Published in
Machine Learning, January 2004
DOI 10.1023/b:mach.0000008082.80494.e0
Authors

Tony van Gestel, Johan A.K. Suykens, Bart Baesens, Stijn Viaene, Jan Vanthienen, Guido Dedene, Bart de Moor, Joos Vandewalle

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 197 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
China 2 1%
Colombia 1 <1%
Malaysia 1 <1%
Netherlands 1 <1%
Italy 1 <1%
Germany 1 <1%
Mexico 1 <1%
Turkey 1 <1%
Other 2 1%
Unknown 181 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 20%
Student > Master 32 16%
Researcher 29 15%
Student > Doctoral Student 12 6%
Student > Bachelor 11 6%
Other 39 20%
Unknown 35 18%
Readers by discipline Count As %
Computer Science 56 28%
Engineering 48 24%
Agricultural and Biological Sciences 5 3%
Earth and Planetary Sciences 5 3%
Business, Management and Accounting 4 2%
Other 32 16%
Unknown 47 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 30 July 2019.
All research outputs
#8,534,528
of 25,371,288 outputs
Outputs from Machine Learning
#344
of 1,225 outputs
Outputs of similar age
#36,568
of 143,822 outputs
Outputs of similar age from Machine Learning
#2
of 7 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,225 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 56% 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 143,822 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.