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Starting from the status of the stock market, this paper points out that there are still many deficiencies in China's stock market, and it is necessary to introduce data mining technique. The chapter 1 focuses on the conceptual theoretical knowledge of data mining process, including the definition and process of data mining technique, as well as the application scope of data mining in stock market. The chapter 2 starts from the application status of cluster analysis in stock market, mainly introduces the definitions and methods of cluster analysis, and then briefly introduces the hierarchical cluster analysis method. Chapter 3 starts from practical examples to illustrate the effectiveness of cluster analysis used in the stock market. Some 40 companies of Henan Province listed in Shanghai and Shenzhen stock market are randomly chosen to help investors find some stocks with characteristics of both low-risk and high-yield, while get a general understanding of the stock price trends. Five indexes, including earnings per share, net assets per share, the main revenue growth, profit growth and the main ROE, are used as the evaluation system, and the stocks of these 40 companies are cluster analyzed using the hierarchical cluster analysis method, so as to analyze the gain, growth and other aspects of these stocks.