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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Gradient boosting machines, a tutorial
|
|---|---|
| Published in |
Frontiers in Neurorobotics, January 2013
|
| DOI | 10.3389/fnbot.2013.00021 |
| Pubmed ID | |
| Authors |
Alexey Natekin, Alois Knoll |
| Abstract |
Gradient boosting machines are a family of powerful machine-learning techniques that have shown considerable success in a wide range of practical applications. They are highly customizable to the particular needs of the application, like being learned with respect to different loss functions. This article gives a tutorial introduction into the methodology of gradient boosting methods with a strong focus on machine learning aspects of modeling. A theoretical information is complemented with descriptive examples and illustrations which cover all the stages of the gradient boosting model design. Considerations on handling the model complexity are discussed. Three practical examples of gradient boosting applications are presented and comprehensively analyzed. |
X Demographics
The data shown below were collected from the profiles of 110 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 | 26 | 24% |
| United Kingdom | 8 | 7% |
| France | 5 | 5% |
| India | 4 | 4% |
| Australia | 3 | 3% |
| Spain | 3 | 3% |
| Japan | 3 | 3% |
| Switzerland | 2 | 2% |
| Canada | 2 | 2% |
| Other | 16 | 15% |
| Unknown | 38 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 80 | 73% |
| Scientists | 27 | 25% |
| Practitioners (doctors, other healthcare professionals) | 2 | 2% |
| Science communicators (journalists, bloggers, editors) | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 2,244 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | <1% |
| United Kingdom | 7 | <1% |
| Japan | 2 | <1% |
| Italy | 2 | <1% |
| China | 2 | <1% |
| Norway | 1 | <1% |
| South Africa | 1 | <1% |
| India | 1 | <1% |
| Brazil | 1 | <1% |
| Other | 8 | <1% |
| Unknown | 2208 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 363 | 16% |
| Student > Master | 300 | 13% |
| Researcher | 215 | 10% |
| Student > Bachelor | 202 | 9% |
| Student > Doctoral Student | 84 | 4% |
| Other | 299 | 13% |
| Unknown | 781 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 389 | 17% |
| Engineering | 286 | 13% |
| Agricultural and Biological Sciences | 91 | 4% |
| Mathematics | 78 | 3% |
| Environmental Science | 65 | 3% |
| Other | 457 | 20% |
| Unknown | 878 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 123. 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 27 September 2023.
All research outputs
#344,678
of 26,017,215 outputs
Outputs from Frontiers in Neurorobotics
#4
of 1,054 outputs
Outputs of similar age
#2,266
of 295,070 outputs
Outputs of similar age from Frontiers in Neurorobotics
#1
of 20 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,054 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 99% 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 295,070 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 99% of its contemporaries.
We're also able to compare this research output to 20 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 95% of its contemporaries.