Abstract
This paper reviews Prof. Kai-Tai Fang’s contributions in data mining. Since the 1970s, Prof. Fang has been committed to applying statistical ideas and methods to deal with large amounts of data in practical projects. By analyzing more than 400,000 pieces of data, he found representative clothing indicators and established the first adult clothing standard in China; through cleaning and modeling steel-making data from steel mills all over the country, he revised the national standard for alloy structural steel; by studying various data in chemometrics, he introduced many new advanced statistical methods to improve the identification and classification of chemical components, established more effective models for the relationship between quantitative structure and activity, and promoted the application of the traditional Chinese medicine (TCM) fingerprint in TCM quality control. Professor Fang and his team’s research achievements in data mining have been highly appreciated by relevant experts. This article is written to celebrate the 80th birthday of Prof. Kaitai Fang.
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Acknowledgments
This work was partially supported by Guangdong Natural Science Foundation (No. 2018A0303130231) and Guangdong Innovation and Enhancement Project: Education Research Programme (R5201920).
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He, P., Peng, X., Xu, Q. (2020). From “Clothing Standard” to “Chemometrics”. In: Fan, J., Pan, J. (eds) Contemporary Experimental Design, Multivariate Analysis and Data Mining. Springer, Cham. https://doi.org/10.1007/978-3-030-46161-4_3
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