Abstract
The results of comparison of quality of two classificators-SVM (support vector machine) and SIMCA (soft independent modelling of class analogies) on model data contained profiles of absorbtion specra of exhalted air are presented. It is shown, that SVM classification results can be improved by preprocessing if input data with principal component analysis method.
Original language | English |
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Title of host publication | 21st International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics |
Publisher | SPIE |
Volume | 9680 |
ISBN (Electronic) | 9781628419085 |
DOIs | |
Publication status | Published - 2015 |
Externally published | Yes |
Event | 21st International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics - Tomsk, Russian Federation Duration: 22 Jun 2015 → 26 Jun 2015 |
Conference
Conference | 21st International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics |
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Country | Russian Federation |
City | Tomsk |
Period | 22.6.15 → 26.6.15 |
Keywords
- gas mixtures analysis
- laser spectroscopy
- Principal component analysis
- SIMCA
- SVM
ASJC Scopus subject areas
- Applied Mathematics
- Computer Science Applications
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics