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A new classification model for a class imbalanced data set using genetic programming and support vector machines: case study for wilt disease classification

Overview of attention for article published in Remote Sensing Letters, June 2015
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About this Attention Score

  • Among the highest-scoring outputs from this source (#40 of 131)
  • Above-average Attention Score compared to outputs of the same age (57th percentile)

Mentioned by

wikipedia
2 Wikipedia pages

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
20 Mendeley
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Title
A new classification model for a class imbalanced data set using genetic programming and support vector machines: case study for wilt disease classification
Published in
Remote Sensing Letters, June 2015
DOI 10.1080/2150704x.2015.1062159
Authors

Muhammad Syafiq Mohd Pozi, Nasir Sulaiman, Norwati Mustapha, Thinagaran Perumal

Timeline

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 5%
United States 1 5%
Unknown 18 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 50%
Student > Master 3 15%
Other 2 10%
Researcher 2 10%
Lecturer > Senior Lecturer 1 5%
Other 1 5%
Unknown 1 5%
Readers by discipline Count As %
Computer Science 5 25%
Environmental Science 2 10%
Earth and Planetary Sciences 2 10%
Engineering 2 10%
Mathematics 1 5%
Other 4 20%
Unknown 4 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 10 September 2023.
All research outputs
#7,630,234
of 23,253,955 outputs
Outputs from Remote Sensing Letters
#40
of 131 outputs
Outputs of similar age
#89,788
of 263,774 outputs
Outputs of similar age from Remote Sensing Letters
#2
of 4 outputs
Altmetric has tracked 23,253,955 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 131 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has gotten more attention than average, scoring higher than 51% 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 263,774 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 57% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.