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On using nearly-independent feature families for high precision and confidence

Overview of attention for article published in Machine Learning, May 2013
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Mentioned by

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1 X user

Citations

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29 Dimensions

Readers on

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54 Mendeley
Title
On using nearly-independent feature families for high precision and confidence
Published in
Machine Learning, May 2013
DOI 10.1007/s10994-013-5377-0
Authors

Omid Madani, Manfred Georg, David Ross

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

Geographical breakdown

Country Count As %
Australia 2 4%
Korea, Republic of 1 2%
United States 1 2%
Spain 1 2%
Unknown 49 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 31%
Researcher 8 15%
Student > Master 6 11%
Student > Bachelor 4 7%
Student > Doctoral Student 3 6%
Other 11 20%
Unknown 5 9%
Readers by discipline Count As %
Computer Science 34 63%
Mathematics 3 6%
Engineering 3 6%
Agricultural and Biological Sciences 3 6%
Arts and Humanities 2 4%
Other 2 4%
Unknown 7 13%
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 02 January 2017.
All research outputs
#15,416,191
of 22,925,760 outputs
Outputs from Machine Learning
#663
of 967 outputs
Outputs of similar age
#120,651
of 195,474 outputs
Outputs of similar age from Machine Learning
#13
of 15 outputs
Altmetric has tracked 22,925,760 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 967 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 20th percentile – i.e., 20% 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 195,474 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.