Wavelet-based classification and influence matrix analysis method for the fast discrimination of Chinese herbal medicines according to the geographical origins with near infrared spectroscopy
作者： Wenlong Li , Haibin Qu
DOI: 10.1142/S1793545813500612
关键词:
摘要: A discriminant analysis technique using wavelet transformation (WT) and influence matrix (CAIMAN) method is proposed for the near infrared (NIR) spectroscopy classification. In methodology, NIR spectra are decomposed by WT data compression a forward feature selection further employed to extract relevant information from coefficients, reducing both classification errors model complexity. discriminant-CAIMAN (D-CAIMAN) utilized build in domain on basis of reduced coefficients spectral variables. set 265 salviae miltiorrhizae radix samples 9 different geographical origins used as an example test performance algorithm. For comparison, k-nearest neighbor (KNN), linear (LDA) quadratic (QDA) methods also employed. D-CAIMAN with wavelet-based (WD-CAIMAN) shows best performance, achieving total rate 100% cross-validation prediction set. It worth noting that WD-CAIMAN classifier improved sensitivity, selectivity interpretability classifications.
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