面向高新企业审计数据的特征选择算法研究

Research on Feature Selection Algorithm for Audit Data of High-new Enterprises

在信息技术快速发展的背景下,庞大的数据经常会给数据的存储和计算带来巨大负担。为提高审计工作的效率和质量,结合特征选择算法和大数据处理技术进行审计数据平台的开发。通过使用二阶段特征选择算法模型,在快速相关滤波特征选择算法(FCBF)的基础上进行改进,使用最大互信息系数衡量特征,引入计算弱相关及冗余性的评价准则。系统面向公司审计数据集,通过特征选择后对样本的创新水平进行分析,实现智能分析的效果。

In the context of the rapid development of information technology,huge data often brings great burden to data storage and calculation.In order to improve the effi ciency and quality of audit work,this paper combines the feature selection algorithm and the big data processing technology to develop the audit data platform.By using the two-stage feature selection algorithm model which is improved on the basis of the fast correlation fi lter feature selection algorithm(FCBF),the characteristics are measured by the maximum mutual information coefficient,and the evaluation criteria for calculating weak correlation and redundancy is introduced.The system is oriented towards the company’s audit data set,and after the characteristic selection,the innovation level of the sample is analyzed to achieve the effect of intelligent analysis.