Probability Bankruptcy Using Support Vector Regression Machines

A. Manurung, Derwin Suhartono, B. Hutahayan, Noptovius Halimawan
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Abstract

Bankruptcy is a decision made by a court after examining the assets and liabilities of individuals even businesses in which they are not able to pay their bills. Due to the importance of prevent bankruptcy to be happened in such business, a calculation which can predict probability bankruptcy is necessary. This paper aims to investigate probability bankruptcy using Support Vector Regression. There are 6 variables for 2016 to 2018 period coming from 17 coal mining companies from Indonesia. The model built by using Support Vector Regression indicates a good performance because it has the highest coefficient of determination.
基于支持向量回归机的概率破产
破产是法院在审查个人甚至企业无力支付账单的资产和负债后作出的决定。由于防止此类企业发生破产的重要性,因此有必要进行破产概率预测的计算。本文旨在利用支持向量回归研究破产概率。2016年至2018年期间有6个变量来自印度尼西亚的17家煤炭开采公司。采用支持向量回归方法建立的模型具有最高的决定系数,具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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