The Application Research Of Association Rules Mining In Stock Forecast

Data mining is the most developing, main and vigorous research content in artificial Intelligence and database research. Association rule mining from large database is new hot point in Data mining. It has venture and opportunity in stock investiture, how to get the most yield and hold the venture? Investor hankered for them. However, stock price was always fluctuant for complex politics and economy. And dependability about stock analysis software need validate. With the development of the stock market, lots of history transaction data have been stored in stock database. It becomes signification using association rule mining technology to analyzed and forecast the stock market.This article based on the domestic and foreign research results, first introduced the theory of data mining and analyzed algorithm Apriori, through the analysis on the insufficiency of the traditional association rule algorithm and specialty in stock data produced an optimized algorithm in frequent items that based on bit vector and hash technology which inserted the data mining tool Weka..Simultaneity, designed and implemented data preprocessing model through analysis stock resource data and Weka data type.Finally explained the process about stock rules using modification Weka and analyzed application merits of stock rules. It supplied a useful reference for stock investor forecast stock eat and flow.