Drug Discrimination Method Based on Near Infrared Reflectance Spectrum and Balance Cascading Sparse Representation Based Classification
LIU Zhen-bing1, GAO Chun-yang1*, YANG Hui-hua1, 2, YIN Li-hui3, FENG Yan-chun3, HU Chang-qin3
1. College of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China 2. Beijing University of Posts and Telecommunications, Beijing 100876, China 3. National Institutes for Food and Drug Control, Beijing 100050, China
Abstract：The combination of near infrared spectrum and pattern recognition methods has a wide application prospect in rapid and nondestructive supervision and management of drugs. The traditional identification methods regard the smallest error rate as the goal while the imbalance of classes is ignored. This makes the positive class is overwhelming covered by the negative class and reduces its effect for the classifier, so that the classification results tend to recognize the negative class correctly, which severely affects the identification accuracy. In this paper, we mainly studied the class imbalance problems of true or false drugs via infrared spectral data of its, and then propose a balance cascading and sparse representation based classification method (BC-SRC) by combining the Balance Cascading with SRC. We sampling majority samples from the majority class for several times, which has the same size as minority samples and the majority samples we sampled can contain all the majority class samples entirely (sampling times is ceiling the result of majority samples number divide minority samples number). We can get sets of results, and then obtain the final predict labels form those results. Experiments of three databases achieved on Matlab2012a shows that the method is effective. From the experimental results, it can be seen that the method is superior to the commonly used Partial Least Squares (PLS), Extreme Learning Machine (ELM) and BP. Particularly, for the imbalanced databases, when the imbalance factor is greater than 10, the proposed method has more stable performance with higher classification accuracy than the existing ones mentioned above.
刘振丙1，高春洋1*，杨辉华1, 2，尹利辉3，冯艳春3，胡昌勤3 . 基于近红外光谱检测和平衡级联稀疏分类的药品鉴别方法 [J]. 光谱学与光谱分析, 2017, 37(02): 435-440.
LIU Zhen-bing1, GAO Chun-yang1*, YANG Hui-hua1, 2, YIN Li-hui3, FENG Yan-chun3, HU Chang-qin3 . Drug Discrimination Method Based on Near Infrared Reflectance Spectrum and Balance Cascading Sparse Representation Based Classification. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(02): 435-440.
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