Classification of Chinese Herbal Medicine Based on Improved LDA Algorithm Using Machine Olfaction

Abstract:

Linear discriminant analysis (LDA) is a popular method among pattern recognition algorithms of machine olfaction. However, “Small Sample Size” (SSS) problem would occur while using LDA algorithm with traditional Fisher criterion if the within-class scatter matrix is singular. In this paper, maximum scatter difference (MSD) criterion and LDA were combined to solve SSS problem, so that three kinds of Chinese herbal medicines from different growing areas were accurately classified. At the same time, the classification result was enhanced. It works out that only a few samples of Anhui Atractylodes are classified incorrectly, however, the classification rate reaches 97.8%.

• Periodical: Applied Mechanics and Materials (Volumes 239-240)
• Pages: 1532-1536
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.239-240.1532
• Online since: December 2012
• Authors: De Han Luo, Ya Wen Shao
• Keywords: Chinese Herbal Medicine, Linear Discriminant Analysis, Machine Olfaction, Maximum Scatter Difference Criterion

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