Principal Model Analysis Based on Bagging PLS and PCA and Its Application in Financial Statement Fraud

作     者：Xiao LIANG Qiwei XIE Chunyan LUO Liang TANG Yi SUN Xiao LIANG;Qiwei XIE;Chunyan LUO;Liang TANG;Yi SUN

作者机构：School of Economics and ManagementBeijing University of TechnologyBeijing 100124China Shanghai Tongtu Semiconductor Technology Co.LtdShanghai 210203China School of FinanceAnhui University of Finance&EconomicsBengbu 233000China 

出 版 物：《Journal of Systems Science and Information》 (系统科学与信息学报（英文）)

年 卷 期：2024年第12卷第2期

页      面：212-228页

核心收录：

学科分类：120202[管理学-企业管理（含：财务管理、市场营销、人力资源管理）] 12[管理学] 1202[管理学-工商管理] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by the Beijing Municipal Social Science Foundation(SZ202210005004) Beijing Natural Science Foundation(9242004) 

主　　题：principal model analysis partial least squares principal component analysis dimension reduction ensemble learning financial statement fraud detection 

摘      要：Motivated by the Bagging Partial Least Squares(Bagging PLS)and Principal Component Analysis(PCA)algorithms,a novel approach known as Principal Model Analysis(PMA)method is introduced in this *** the proposed PMA algorithm,the PCA and the Bagging PLS are *** this method,multiple PLS models are trained on sub-training sets,derived from the training set using the random sampling with replacement *** regression coefficients of all the sub-PLS models are fused in a joint regression coefficient *** final projection direction is then estimated by performing the PCA on the joint regression coefficient ***,the proposed PMA method is compared with other traditional dimension reduction methods,such as PLS,Bagging PLS,Linear discriminant analysis(LDA)and *** results on six public datasets demonstrate that our proposed method consistently outperforms other approaches in terms of classification performance and exhibits greater ***,it is employed in the application of financial statement fraud *** and other five algorithms are utilized to financial statement fraud which concerned by the academic community,and the results indicate that the classification of PMA surpassed that of the other methods.