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Cost-Constrained feature selection in binary classification: adaptations for greedy forward selection and genetic algorithms

Overview of attention for article published in BMC Bioinformatics, January 2020
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Mentioned by

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1 X user

Citations

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22 Dimensions

Readers on

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19 Mendeley
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Title
Cost-Constrained feature selection in binary classification: adaptations for greedy forward selection and genetic algorithms
Published in
BMC Bioinformatics, January 2020
DOI 10.1186/s12859-020-3361-9
Pubmed ID
Authors

Rudolf Jagdhuber, Michel Lang, Arnulf Stenzl, Jochen Neuhaus, Jörg Rahnenführer

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 32%
Student > Ph. D. Student 3 16%
Student > Doctoral Student 2 11%
Lecturer 1 5%
Researcher 1 5%
Other 1 5%
Unknown 5 26%
Readers by discipline Count As %
Computer Science 5 26%
Engineering 3 16%
Medicine and Dentistry 2 11%
Physics and Astronomy 1 5%
Biochemistry, Genetics and Molecular Biology 1 5%
Other 2 11%
Unknown 5 26%
Attention Score in Context

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 28 January 2020.
All research outputs
#18,709,638
of 23,189,371 outputs
Outputs from BMC Bioinformatics
#6,380
of 7,345 outputs
Outputs of similar age
#330,200
of 451,467 outputs
Outputs of similar age from BMC Bioinformatics
#142
of 180 outputs
Altmetric has tracked 23,189,371 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,345 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 5th percentile – i.e., 5% 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 451,467 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 180 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.