Tianyang Xu, Juan Yang, Xiaorong Sun, Cuiling Liu, Yi Li, Jinhui Zhou, Lanzhen Chen. Mid-Infrared Spectroscopy Analysis Combined with Support Vector Machine for Rapid Discrimination of Botanical Origin of Honey[J]. Laser & Optoelectronics Progress, 2018, 55(6): 063003
- Laser & Optoelectronics Progress
- Vol. 55, Issue 6, 063003 (2018)
Fig. 1. Mid-infrared spectra of different honey samples
Fig. 2. Actual and predicted classifications of test set using SVM algorithm when recognition rate is 100% and 20-dimensional feature data are input
Fig. 3. Actual and predicted classifications of test set using SVM algorithm when recognition rate is 99.23% and 20-dimensional feature data are input
Fig. 4. Actual and predicted classifications of test set using LSSVM algorithm when recognition rate is 100% and 20-dimensional feature data are input
Fig. 5. Actual and prediction classifications of test set using LSSVM algorithm when recognition rate is 97.69% and 20-dimensional feature data are input
Fig. 6. Transformation graph of support vector from 1-dimensional space to 2-dimensional space
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Table 1. Cumulative variance contribution rate of different principal components
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Table 2. Average discrimination rate of different dimension feature data from linear SVM and LSSVM classifier models%
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