A Strong Classifier Model for Listed Companies Financial Risk Warning

被引：2

作者：

Sun Jing ^{[1
]}

Xinyan-Li ^{[1
]}

Niu Jun-Jie ^{[1
]}

机构：

[1] Qingdao Vocat & Tech Coll Hotel Management, Qingdao 266100, Shandong, Peoples R China

来源：

2015 SEVENTH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA 2015) | 2015年

关键词：

AdabooostSVM; classifier; listed companies; T-test;

D O I：

10.1109/ICMTMA.2015.22

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Existing measures and prediction effects for the listed companies financial risk have instability. By the research on strong classifier models, we adopt Adaboost algorithm which can improve any weak learner to strong one to solve the problems. It is integrated with support vector machine to establish the warning model and study the financial warning states of domestic listed companies. The scheme takes SVM based on linear kernel function as the component classifier of Adaboost and changes the kernel function of the component classifier during the learning process. So such integration can obviously improve the performance of classifier and obtain AdaBoostSVM classifier with stronger classification ability. The experiments demonstrate that, compared to single SVM, AdaBoostSVM makes an improvement for 70 test samples of 4% in classification, which shows better application value in the research of listed warning..

引用

页码：59 / 63

页数：5