id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fbem-7557	Chen, Yinhe	Financial Statement Fraud Detection based on Integrated Feature Selection and Imbalance Learning	2023	3	.pdf	application/pdf	1865	104	51	2. Literature References The study of financial statement fraud often carried out the empirical analysis of financial statement fraud enterprises, so as to analyze the signals of financial statement fraud in listed companies for auditors and investors. The integrated feature selection framework proposed in this paper improves the problem of poor generalization of the single feature selection method, and the SMOTE effectively strengthens and improves the ability of the model to detect financial statement fraud of listed companies.	cache/fbem-7557.pdf	txt/fbem-7557.txt