Interpreting support vector machines applied in laser-induced breakdown spectroscopy

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F22%3APU142522" target="_blank" >RIV/00216305:26620/22:PU142522 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14310/22:00126745
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0003267021011788#appsec1" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0003267021011788#appsec1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.aca.2021.339352" target="_blank" >10.1016/j.aca.2021.339352</a>

Result language
angličtina
Original language name
Interpreting support vector machines applied in laser-induced breakdown spectroscopy
Original language description
Laser-induced breakdown spectroscopy is often combined with a multivariate black box model—such as support vector machines (SVMs)—to obtain desirable quantitative or qualitative results. This approach carries obvious risks when practiced in high-stakes applications. Moreover, the lack of understanding of a black-box model limits the user's ability to fine-tune the model. Thus, here we present four approaches to interpret SVMs through investigating which features the models consider important in the classification task of 19 algal and cyanobacterial species. The four feature importance metrics are compared with popular approaches to feature selection for optimal SVM performance. We report that the distinct feature importance metrics yield complementary and often comparable information. In addition, we identify our SVM model's bias towards features with a large variance, even though these features exhibit a significant overlap between classes. We also show that the linear and radial basis kernel SVMs weight the same features to the same degree.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10406 - Analytical chemistry

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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