Laser & Optoelectronics Progress, Volume. 56, Issue 4, 043003(2019)
Raman Spectroscopic Classification of Foodborne Pathogenic Bacteria Based on PCA-Stacking Model
The rapid identification of foodborne pathogenic bacteria is an important task. Compared with the traditional detection methods, Raman spectroscopy is a non-destructive testing method and can simultaneously enhance the identification speed. In order to improve the accuracy and efficiency of Raman spectroscopic identification of Escherichia coil O157∶H7 and Brucella suis vaccine strain S2, a integral classification model is proposed based on the principal component analysis and the Stacking algorithm, whose robustness is improved by the grid search and K-fold cross validation. It is experimentally confirmed that compared with the logistic regression, K nearest neighbor, support vector machine and other single models, the integral model based on the Stacking algorithm possesses the highest accuracy rate of 99.73% the expected result is achieved.
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Rujin Shi, Fanzeng Xia, Wandan Zeng, Han Qu. Raman Spectroscopic Classification of Foodborne Pathogenic Bacteria Based on PCA-Stacking Model[J]. Laser & Optoelectronics Progress, 2019, 56(4): 043003
Category: Spectroscopy
Received: Jun. 27, 2018
Accepted: Sep. 6, 2018
Published Online: Jul. 31, 2019
The Author Email: Zeng Wandan (zengwd@sit.edu.cn)