| Title |
Choosing Multiple Parameters for Support Vector Machines
|
|---|---|
| Published in |
Machine Learning, January 2002
|
| DOI | 10.1023/a:1012450327387 |
| Authors |
Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee |
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 % |
|---|---|---|
| Saudi Arabia | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 589 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 14 | 2% |
| Germany | 10 | 2% |
| France | 7 | 1% |
| China | 5 | <1% |
| Netherlands | 3 | <1% |
| Italy | 3 | <1% |
| Turkey | 2 | <1% |
| Chile | 2 | <1% |
| Colombia | 2 | <1% |
| Other | 15 | 3% |
| Unknown | 526 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 156 | 26% |
| Student > Master | 88 | 15% |
| Researcher | 76 | 13% |
| Student > Bachelor | 37 | 6% |
| Student > Doctoral Student | 35 | 6% |
| Other | 100 | 17% |
| Unknown | 97 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 240 | 41% |
| Engineering | 109 | 19% |
| Agricultural and Biological Sciences | 24 | 4% |
| Mathematics | 15 | 3% |
| Earth and Planetary Sciences | 12 | 2% |
| Other | 66 | 11% |
| Unknown | 123 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 22 February 2024.
All research outputs
#3,622,393
of 25,374,917 outputs
Outputs from Machine Learning
#94
of 1,225 outputs
Outputs of similar age
#8,232
of 130,776 outputs
Outputs of similar age from Machine Learning
#2
of 8 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,225 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 92% 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 130,776 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 93% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.