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 

机构地区：[1]School of Economics and Management,Beijing University of Technology,Beijing 100124,China [2]Shanghai Tongtu Semiconductor Technology Co.,Ltd,Shanghai 210203,China [3]School of Finance,Anhui University of Finance&Economics,Bengbu 233000,China

出　　处：《Journal of Systems Science and Information》2024年第2期212-228,共17页系统科学与信息学报（英文）

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

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 paper.In the proposed PMA algorithm,the PCA and the Bagging PLS are combined.In this method,multiple PLS models are trained on sub-training sets,derived from the training set using the random sampling with replacement approach.The regression coefficients of all the sub-PLS models are fused in a joint regression coefficient matrix.The final projection direction is then estimated by performing the PCA on the joint regression coefficient matrix.Subsequently,the proposed PMA method is compared with other traditional dimension reduction methods,such as PLS,Bagging PLS,Linear discriminant analysis(LDA)and PLS-LDA.Experimental results on six public datasets demonstrate that our proposed method consistently outperforms other approaches in terms of classification performance and exhibits greater stability.Additionally,it is employed in the application of financial statement fraud identification.PMA 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.

关 键 词：principal model analysis partial least squares principal component analysis dimension reduction ensemble learning financial statement fraud detection 

分 类 号：F275[经济管理—企业管理] TP18[经济管理—国民经济]