↓ Skip to main content

CSViz: Class Separability Visualization for high-dimensional datasets

Overview of attention for article published in Applied Intelligence, December 2023
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#19 of 2,076)
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

twitter
11 X users

Readers on

mendeley
2 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
CSViz: Class Separability Visualization for high-dimensional datasets
Published in
Applied Intelligence, December 2023
DOI 10.1007/s10489-023-05149-4
Authors

Marina Cuesta, Carmen Lancho, Alberto Fernández-Isabel, Emilio L. Cano, Isaac Martín De Diego

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Unknown 1 50%
Readers by discipline Count As %
Business, Management and Accounting 1 50%
Unknown 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 12 January 2024.
All research outputs
#3,741,990
of 25,732,188 outputs
Outputs from Applied Intelligence
#19
of 2,076 outputs
Outputs of similar age
#54,815
of 354,911 outputs
Outputs of similar age from Applied Intelligence
#2
of 32 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,076 research outputs from this source. They receive a mean Attention Score of 1.0. This one has done particularly well, scoring higher than 99% 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 354,911 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 84% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.