多状态指数优化指导下的财务数据关键特征挖掘

研究一种引入多状态指数优化指导下的财务数据关键特征挖掘方法;对海量财务数据关键特征的挖掘是现代海量数据形势下快速信息挖掘的重要方法;传统的海量财务数据挖掘一般采用特征挖掘方法。文中针对财务数据关键的普通特征挖掘、特征分布考虑不足,无法实现深度特征挖掘问题。提出一种引入多状态指数优化指导的财务数据关键特征挖掘方法,对财务数据特征进行更加细致的挖掘,提取深度财务数据特征;最后采用一组特征接近的词汇进行财务数据特征挖掘实验,结果显示,文中方法将财务数据关键特征有效地区分开来,具有一定实用性。

Key Feature Mining of Financial Data with Optimization Guidance of Multi-state Index

Introduced the research a kind of state index optimization under the guidance of key characteristics of the financial data mining method; The key characteristics of the massive financial data mining is the modem mass da- ta situation, fast information necessary for mining method ; Traditional mass financial data mining methods the gener- al characteristics of the mining method, common characteristics of key financial data mining, the lack of considering the characteristics of financial data distribution, unable to realize the characteristics of deep mining; Proposed a state introduced the index optimization guide the key features of the financial data mining method, by introducing the idea of multiple state index optimization guidance to guide the key to the massive financial data mining, to more de- tailed financial data characteristics of digging, to extract the depth of the financial data; Finally USES a set of fea- tures close vocabulary in financial data mining experiment, the results show that, based on the introduction of more state index optimization with the mining method of guidance, financial data is good apart from the key characteristic and has extensive value of application.