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Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms

Overview of attention for article published in BMC Bioinformatics, September 2010
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Mentioned by

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2 X users

Citations

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69 Dimensions

Readers on

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242 Mendeley
citeulike
7 CiteULike
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Title
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms
Published in
BMC Bioinformatics, September 2010
DOI 10.1186/1471-2105-11-447
Pubmed ID
Authors

Yu Guo, Armin Graber, Robert N McBurney, Raji Balasubramanian

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 242 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 3%
United Kingdom 4 2%
Austria 1 <1%
Australia 1 <1%
Brazil 1 <1%
Germany 1 <1%
South Africa 1 <1%
Malaysia 1 <1%
Sweden 1 <1%
Other 1 <1%
Unknown 223 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 58 24%
Student > Ph. D. Student 45 19%
Student > Master 29 12%
Professor > Associate Professor 19 8%
Professor 18 7%
Other 47 19%
Unknown 26 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 58 24%
Medicine and Dentistry 27 11%
Computer Science 23 10%
Engineering 21 9%
Biochemistry, Genetics and Molecular Biology 19 8%
Other 52 21%
Unknown 42 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 28 March 2022.
All research outputs
#14,640,894
of 23,435,471 outputs
Outputs from BMC Bioinformatics
#4,788
of 7,388 outputs
Outputs of similar age
#75,829
of 96,055 outputs
Outputs of similar age from BMC Bioinformatics
#37
of 52 outputs
Altmetric has tracked 23,435,471 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,388 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 96,055 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.