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The behaviour of random forest permutation-based variable importance measures under predictor correlation

Overview of attention for article published in BMC Bioinformatics, February 2010
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

googleplus
1 Google+ user

Citations

dimensions_citation
192 Dimensions

Readers on

mendeley
296 Mendeley
citeulike
4 CiteULike
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Title
The behaviour of random forest permutation-based variable importance measures under predictor correlation
Published in
BMC Bioinformatics, February 2010
DOI 10.1186/1471-2105-11-110
Pubmed ID
Authors

Kristin K Nicodemus, James D Malley, Carolin Strobl, Andreas Ziegler

Mendeley readers

The data shown below were compiled from readership statistics for 296 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 1%
Colombia 2 <1%
Italy 2 <1%
Turkey 2 <1%
Canada 2 <1%
United Kingdom 2 <1%
Germany 2 <1%
Spain 2 <1%
Greece 2 <1%
Other 7 2%
Unknown 269 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 91 31%
Researcher 67 23%
Student > Master 40 14%
Student > Doctoral Student 19 6%
Student > Bachelor 17 6%
Other 39 13%
Unknown 23 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 68 23%
Environmental Science 39 13%
Computer Science 31 10%
Mathematics 24 8%
Engineering 24 8%
Other 64 22%
Unknown 46 16%

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 09 January 2017.
All research outputs
#7,762,546
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#3,172
of 4,576 outputs
Outputs of similar age
#192,296
of 346,756 outputs
Outputs of similar age from BMC Bioinformatics
#288
of 423 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 21st percentile – i.e., 21% 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 346,756 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 423 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.