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Attention Score in Context
Title |
Cross-validation pitfalls when selecting and assessing regression and classification models
|
---|---|
Published in |
Journal of Cheminformatics, March 2014
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DOI | 10.1186/1758-2946-6-10 |
Pubmed ID | |
Authors |
Damjan Krstajic, Ljubomir J Buturovic, David E Leahy, Simon Thomas |
Abstract |
We address the problem of selecting and assessing classification and regression models using cross-validation. Current state-of-the-art methods can yield models with high variance, rendering them unsuitable for a number of practical applications including QSAR. In this paper we describe and evaluate best practices which improve reliability and increase confidence in selected models. A key operational component of the proposed methods is cloud computing which enables routine use of previously infeasible approaches. |
X Demographics
The data shown below were collected from the profiles of 27 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 22% |
India | 2 | 7% |
Spain | 2 | 7% |
Brazil | 2 | 7% |
Finland | 1 | 4% |
Netherlands | 1 | 4% |
Canada | 1 | 4% |
Australia | 1 | 4% |
Greece | 1 | 4% |
Other | 2 | 7% |
Unknown | 8 | 30% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 20 | 74% |
Scientists | 6 | 22% |
Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 744 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 5 | <1% |
United States | 4 | <1% |
Brazil | 3 | <1% |
United Kingdom | 3 | <1% |
Italy | 1 | <1% |
Ecuador | 1 | <1% |
Malaysia | 1 | <1% |
Sweden | 1 | <1% |
Finland | 1 | <1% |
Other | 6 | <1% |
Unknown | 718 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 153 | 21% |
Student > Master | 124 | 17% |
Researcher | 112 | 15% |
Student > Bachelor | 61 | 8% |
Student > Doctoral Student | 41 | 6% |
Other | 106 | 14% |
Unknown | 147 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 119 | 16% |
Engineering | 92 | 12% |
Agricultural and Biological Sciences | 67 | 9% |
Chemistry | 52 | 7% |
Medicine and Dentistry | 42 | 6% |
Other | 201 | 27% |
Unknown | 171 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 27. 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 01 December 2021.
All research outputs
#1,363,772
of 24,751,485 outputs
Outputs from Journal of Cheminformatics
#76
of 923 outputs
Outputs of similar age
#13,461
of 230,672 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 22 outputs
Altmetric has tracked 24,751,485 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 923 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has done particularly well, scoring higher than 91% 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 230,672 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 22 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 99% of its contemporaries.