数据挖掘在数据分析中的应用

R. Chen
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引用次数: 0

摘要

在新时代背景下,计算机硬件规模和系统复杂程度开始发生变化,市场上出现了超大容量存储设备和多核CPU,使得在计算机上存储和处理海量信息成为可能。然而,仅靠软件开发并不能解决现实中的技术问题。因此,研究者根据实践和探索中的复杂数据,深入探讨了如何建立一种有效的方法来处理和利用现有的数据信息,使其在所有企业中发挥应有的作用。因此,本文在了解数据挖掘的概念及其内容形式的基础上,以电能质量监测数据分析为例,主要探讨了如何将隐含数据挖掘技术算法应用到数据分析中。实验结果表明,数据挖掘在数据分析中是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The application of data mining in data analysis
In the context of the new era, the scale of computer hardware and system complexity began to change, the emergence of super-capacity storage equipment and multi-core CPU in the market, which makes it possible to store and process massive information on the computer. However, software development alone cannot solve the technical problems in reality. Therefore, according to the complex data in practice and exploration, researchers deeply discuss how to establish an effective method to process and use the existing data information, so that it can play its due role in all enterprises. Therefore, on the basis of understanding the concept of data mining and its content form, this paper mainly discusses how to apply embodied data mining technology algorithm in data analysis, taking power quality monitoring data analysis as an example. The experimental results show that data mining is effective in data analysis.
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