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X Demographics
Mendeley readers
Attention Score in Context
| Title |
PROPER: Performance visualization for optimizing and comparing ranking classifiers in MATLAB
|
|---|---|
| Published in |
Source Code for Biology and Medicine, December 2015
|
| DOI | 10.1186/s13029-015-0047-1 |
| Pubmed ID | |
| Authors |
Samad Jahandideh, Fatemeh Sharifi, Lukasz Jaroszewski, Adam Godzik |
| Abstract |
One of the recent challenges of computational biology is development of new algorithms, tools and software to facilitate predictive modeling of big data generated by high-throughput technologies in biomedical research. To meet these demands we developed PROPER - a package for visual evaluation of ranking classifiers for biological big data mining studies in the MATLAB environment. PROPER is an efficient tool for optimization and comparison of ranking classifiers, providing over 20 different two- and three-dimensional performance curves. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 7% |
| Unknown | 14 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 40% |
| Student > Ph. D. Student | 3 | 20% |
| Student > Master | 3 | 20% |
| Student > Bachelor | 2 | 13% |
| Lecturer | 1 | 7% |
| Other | 0 | 0% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 4 | 27% |
| Computer Science | 4 | 27% |
| Agricultural and Biological Sciences | 1 | 7% |
| Mathematics | 1 | 7% |
| Philosophy | 1 | 7% |
| Other | 4 | 27% |
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 04 December 2015.
All research outputs
#20,297,343
of 22,834,308 outputs
Outputs from Source Code for Biology and Medicine
#111
of 127 outputs
Outputs of similar age
#324,915
of 387,656 outputs
Outputs of similar age from Source Code for Biology and Medicine
#5
of 6 outputs
Altmetric has tracked 22,834,308 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 1st percentile – i.e., 1% 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 387,656 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one.