Application of Machine Learning Algorithms in Audit Data Analysis

Jianyu Zhou
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Abstract

In recent years, with the rapid development of information technology, computer technology and the Internet, various sectors of society have collected a large amount of data. At present, traditional statistical analysis models have limitations. Machine learning system is currently one of the main means to effectively solve problems such as data development and mining. Machine learning is a process of self-improvement using the computer system itself. Therefore, computer applications written by computers can be automated by accumulating practical experience. This article aims to study the application of machine learning algorithms in audit data analysis. Based on the analysis of audit information construction, audit data analysis system design principles, and audit data analysis system non-functional requirements analysis, the audit data analysis system is designed. The association rule algorithm in machine learning is used in audit data mining. Finally, the performance of the system is tested. The test results show that the performance of the system designed in this paper is unified with the pre-demand, which shows that the effectiveness of the system can be satisfied.
机器学习算法在审计数据分析中的应用
近年来,随着信息技术、计算机技术和互联网的飞速发展,社会各界收集了大量的数据。目前,传统的统计分析模型存在局限性。机器学习系统是目前有效解决数据开发和挖掘等问题的主要手段之一。机器学习是一个利用计算机系统自身进行自我完善的过程。因此,由计算机编写的计算机应用程序可以通过积累实际经验实现自动化。本文旨在研究机器学习算法在审计数据分析中的应用。在分析审计信息化建设、审计数据分析系统设计原则、审计数据分析系统非功能需求分析的基础上,设计了审计数据分析系统。将机器学习中的关联规则算法应用到审计数据挖掘中。最后,对系统的性能进行了测试。测试结果表明,本文设计的系统性能与预需求基本一致,表明系统的有效性能够得到满足。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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