A genetic algorithm approach for SMEs bankruptcy prediction: Empirical evidence from Italy

作者：

Highlights：

• GAs are a very promising method in SMEs default prediction analysis.

• GAs are capable of extracting rules that are easy to understand for users.

• GAs give a better SMEs default prediction accuracy rate compared with SVM and LR.

• GAs significantly reduce misclassification costs compared to SVM and LR.

• The prediction accuracy rate of GAs is markedly higher for the smallest sized firms and in the firms operating in the north.

摘要

•GAs are a very promising method in SMEs default prediction analysis.•GAs are capable of extracting rules that are easy to understand for users.•GAs give a better SMEs default prediction accuracy rate compared with SVM and LR.•GAs significantly reduce misclassification costs compared to SVM and LR.•The prediction accuracy rate of GAs is markedly higher for the smallest sized firms and in the firms operating in the north.

论文关键词：Genetic algorithms,Support vector machine,Logistic regression,Default prediction modeling,Small and medium sized enterprises

论文评审过程：Available online 2 May 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.04.026