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Hellinger distance-based stable sparse feature selection for high-dimensional class-imbalanced data

Overview of attention for article published in BMC Bioinformatics, March 2020
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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 (76th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

blogs
1 blog
twitter
2 tweeters

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
16 Mendeley
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Title
Hellinger distance-based stable sparse feature selection for high-dimensional class-imbalanced data
Published in
BMC Bioinformatics, March 2020
DOI 10.1186/s12859-020-3411-3
Pubmed ID
Authors

Guang-Hui Fu, Yuan-Jiao Wu, Min-Jie Zong, Jianxin Pan

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 50%
Other 1 6%
Lecturer > Senior Lecturer 1 6%
Lecturer 1 6%
Researcher 1 6%
Other 0 0%
Unknown 4 25%
Readers by discipline Count As %
Computer Science 4 25%
Mathematics 3 19%
Biochemistry, Genetics and Molecular Biology 1 6%
Economics, Econometrics and Finance 1 6%
Decision Sciences 1 6%
Other 2 13%
Unknown 4 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 11 April 2020.
All research outputs
#2,912,285
of 17,415,680 outputs
Outputs from BMC Bioinformatics
#1,196
of 6,159 outputs
Outputs of similar age
#66,018
of 277,046 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 15 outputs
Altmetric has tracked 17,415,680 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,159 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 80% 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 277,046 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.