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From “Clothing Standard” to “Chemometrics”

Review of Prof. Kai-Tai Fang’s Contributions in Data Mining
  • Ping HeEmail author
  • Xiaoling Peng
  • Qingsong Xu
Chapter
  • 83 Downloads

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.

Notes

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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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Beijing Normal University and Hong Kong Baptist University United International CollegeZhuhaiChina
  2. 2.Department of Mathematics and StatisticsCentral South UniversityChangshaChina

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