文章基本信息

标题：KNOWLEDGE STRUCTURE FOR FRAUDULENT FIRM CLASSIFICATION APPROACHES
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作者：Dr.G.Ayyappan ; Dr.A.Kumaravel
期刊名称：Indian Journal of Computer Science and Engineering
印刷版ISSN：2231-3850
电子版ISSN：0976-5166
出版年度：2019
卷号：10
期号：4
页码：89-96
DOI：10.21817/indjcse/2019/v10i4/191004008
出版社：Engg Journals Publications
摘要：Machine learning gives most impact in developing the qualities of an audit work in the futuredue to enormous development of financial fraud. Here, seven hundred and seventy seven firm’s data infourteen different sectors are collected in this research study. This work proposed number ofclassification models are estimated in terms of their accuracies and time taken to build the models. Theresults of Trees and Rules are demonstrating an accuracy of high level for suspicious firm classification.This paper focuses improving the worth of an audit work by implementing a machine learningalgorithms.
关键词：J48; Fraudulent Firm; Audit data; Machine Learning