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Determining threshold value on information gain feature selection to increase speed and prediction accuracy of random forest

Overview of attention for article published in Journal of Big Data, June 2021
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
1 X user
patent
1 patent

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
98 Mendeley
Title
Determining threshold value on information gain feature selection to increase speed and prediction accuracy of random forest
Published in
Journal of Big Data, June 2021
DOI 10.1186/s40537-021-00472-4
Authors

Maria Irmina Prasetiyowati, Nur Ulfa Maulidevi, Kridanto Surendro

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 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 98 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 7%
Student > Ph. D. Student 7 7%
Student > Bachelor 5 5%
Lecturer 4 4%
Unspecified 3 3%
Other 11 11%
Unknown 61 62%
Readers by discipline Count As %
Computer Science 23 23%
Engineering 5 5%
Unspecified 3 3%
Business, Management and Accounting 2 2%
Agricultural and Biological Sciences 2 2%
Other 4 4%
Unknown 59 60%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 05 October 2023.
All research outputs
#7,099,990
of 24,682,395 outputs
Outputs from Journal of Big Data
#120
of 370 outputs
Outputs of similar age
#146,545
of 438,313 outputs
Outputs of similar age from Journal of Big Data
#7
of 17 outputs
Altmetric has tracked 24,682,395 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 370 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.5. This one has gotten more attention than average, scoring higher than 66% 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 438,313 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.