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The Study on Gray Data Mining Model

机译:灰色数据挖掘模型研究

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摘要

Nowadays, most people rely on traditional data mining techniques to address business affairs. But data mining is proposed for the large amount of data, lack of effective methods to process the data that is little or incomplete, or is overall complex but has a strong regularity at a certain time or space. Grey system theory is the new method to research less data, poor information and uncertainty problem. It just makes up for the shortcomings of traditional data mining. Therefore, this paper is to combine gray system theory with data mining technology, study and improve the gray relational data mining model, and as the basic for the establishment of a gray clustering mining model. At last, this paper applies the gray data mining model to the comparison of the securities companies' core competitiveness, thus proving the correctness and effectiveness of the model.
机译:如今,大多数人都依靠传统的数据挖掘技术来解决业务事务。但是,提出了针对大量数据,缺乏有效的方法来处理数据的方法,该方法很少或不完整,或者总体上很复杂,但在特定时间或空间具有很强的规律性。灰色系统理论是研究数据少,信息差和不确定性问题的新方法。它只是弥补了传统数据挖掘的不足。因此,本文将灰色系统理论与数据挖掘技术相结合,研究和完善灰色关联数据挖掘模型,作为建立灰色聚类挖掘模型的基础。最后,将灰色数据挖掘模型应用于证券公司核心竞争力的比较,证明了该模型的正确性和有效性。

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