数据挖掘与数量经济学

The Relation between Data Mining and Econometrics

数据挖掘就是从大量的、不完全的、有噪声的、模糊的、随机的数据中,提取隐含在其中的、人们事先不知道的、但又是潜在的有用信息和知识的过程。它是一个涉及多学科领域的新兴学科,并随着这些学科的发展而不断发展。针对信息化社会的迫切需要,本文从数量经济学和数据挖掘的概念出发,深入地分析了这两个领域的联系与区别,详细地探讨了结合数据挖掘乃至人工智能理论来研究数量经济的思路,为积极推动数量经济学的进一步发展提供了可行的研究方法.

Data mining is the process of abstracting unaware, potential and useful information and knowledge from plentiful, incomplete, noisy, fuzzy and stochastic data. It is such a new and uprising subject that involves a large number of fields. Meantime, it develops with these subjects. In order to satisfy the stringent requirements of information society, this paper analyzes the relation between econometrics and data mining in depth based on the concepts of those two fields. Then the idea that econometric is studied related to data mining even artificial intelligence is discussed in detail, which provide the feasible research methods for the further development of econometrics.