基于决策树的股市数据挖掘与仿真  

Data Mining and Simulation in Stock Market Based on Decision Tree

作　　者：邹筱梅[1] 姜山[1] 唐贤瑛[1] 

机构地区：[1]长沙交通学院计算机工程系,湖南长沙410076

出　　处：《计算机仿真》2004年第3期127-129,共3页Computer Simulation

摘　　要：决策树方法是数据挖掘的一种方便而实用的方法。该文基于对股市数据的分析 ,适当选取某些经济指标作为决策属性 ,并利用改进的ID3算法 ,从股市数据中挖掘获利能力规则。该文提出的算法用C语言编程实现。仿真的结果表明 ,不仅获得了具有应用价值的股市决策规则 ,而且显示出股市中有的经验规则未必正确。Decision tree is a convenient and practical method for data mining. In this paper, some economic targets are selected suitably as decision attribute based on data analysis in stock market. An improved ID3 algorithm is applied to extract earnings rules in stock market. The algorithm presented in this paper is implemented with C language program. Simulating results show not only the obtained meaningful decision rules in stock market, but also the experience rules that are not necessarily correct.

关 键 词：股票市场 数据挖掘 仿真 决策树 归纳学习方法 

分 类 号：F830.91[经济管理—金融学]