数据挖掘方法在股价预测中的应用与效果分析

at t racted t he at t ent i on of many i nvest ors. Therefore, an analysis and forecast of stock prices i s necessary. However, due t o t he i nfl uence of various factors such as pol i cy and economy, i t i s very di fficult t o forecast the price of stocks. In recent years, data mining has developed rapidl y and has become a hot research topic in many f i el ds such as machi ne learning and statistics. Data mining methods have become one of the hottest technologies in t he era of big data. With the i n-depth research of people, many di fferent types of powerful data mining al gorithms have been developed, and many data mining tools have emerged, making data mining simpler and more effi cient. This has greatly expanded the appl i cat i on fi elds of data mining, and stock market price forecast i s one of them. Many companies and research i nstitutes are committed t o stud ying the future trend of stock prices using data mining technology. This paper wi ll i ntroduce several commonl y used classification data mining methods in social product i on and sci ence research, including multivariate statistical analysis, support vector machine, neural network, et c. And their appl ication and forecast eff ectiveness i n stock price predi ction, hoping t o provide some inspiration for people. Key words: data mining, stock price forecast, multivariate statistical analysis, neural network, support vector machine.