| Title |
Cost-sensitive boosting algorithms: Do we really need them?
|
|---|---|
| Published in |
Machine Learning, August 2016
|
| DOI | 10.1007/s10994-016-5572-x |
| Authors |
Nikolaos Nikolaou, Narayanan Edakunni, Meelis Kull, Peter Flach, Gavin Brown |
X Demographics
The data shown below were collected from the profiles of 3 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 Kingdom | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Poland | 1 | 1% |
| Unknown | 87 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 18% |
| Researcher | 13 | 15% |
| Student > Master | 11 | 13% |
| Student > Doctoral Student | 6 | 7% |
| Student > Bachelor | 6 | 7% |
| Other | 20 | 23% |
| Unknown | 16 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 38 | 43% |
| Engineering | 8 | 9% |
| Environmental Science | 3 | 3% |
| Decision Sciences | 3 | 3% |
| Social Sciences | 3 | 3% |
| Other | 8 | 9% |
| Unknown | 25 | 28% |
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 13 May 2019.
All research outputs
#13,031,932
of 22,961,203 outputs
Outputs from Machine Learning
#482
of 967 outputs
Outputs of similar age
#192,212
of 367,545 outputs
Outputs of similar age from Machine Learning
#6
of 10 outputs
Altmetric has tracked 22,961,203 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% 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 48th percentile – i.e., 48% 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 367,545 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.