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 |
|---|---|
| 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 |
|---|---|
| Country | Russian Federation |
| City | Tomsk |
| Period | 22.6.15 → 26.6.15 |
Fingerprint
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
Cite this
Comparison of classification methods used for analysis of complex biological gas mixtures by means of laser spectroscopy. / Kistenev, Y. V.; Shapovalov, A. V.; Vrazhnov, D. A.; Nikolaev, V. V.; Nikiforova, O. Y.
21st International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics. Vol. 9680 SPIE, 2015. 968049.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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TY - GEN
T1 - Comparison of classification methods used for analysis of complex biological gas mixtures by means of laser spectroscopy
AU - Kistenev, Y. V.
AU - Shapovalov, A. V.
AU - Vrazhnov, D. A.
AU - Nikolaev, V. V.
AU - Nikiforova, O. Y.
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
KW - gas mixtures analysis
KW - laser spectroscopy
KW - Principal component analysis
KW - SIMCA
KW - SVM
UR - http://www.scopus.com/inward/record.url?scp=84963614495&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84963614495&partnerID=8YFLogxK
U2 - 10.1117/12.2205777
DO - 10.1117/12.2205777
M3 - Conference contribution
AN - SCOPUS:84963614495
VL - 9680
BT - 21st International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics
PB - SPIE
ER -