Bankruptcy Prediction of Engineering Companies in the EU Using Classification Methods

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This article focuses on the problem of binary classification of 902 small-and medium-sized engineering companies active in the EU, together with additional 51 companies which went bankrupt in 2014. For classification purposes, the basic statistical method of logistic regression has been selected, together with a representative of machine learning (support vector machines and classification trees method) to construct models for bankruptcy prediction. Different settings have been tested for each method. Furthermore, the models were estimated based on complete data and also using identified artificial factors. To evaluate the quality of prediction we observe not only the total accuracy with the type I and II errors but also the area under ROC curve criterion. The results clearly show that increasing distance to bankruptcy decreases the predictive ability of all models. The classification tree method leads us to rather simple models. The best classification results were achieved through logistic regression based on artificial factors. Moreover, this procedure provides good and stable results regardless of other settings. Artificial factors also seem to be a suitable variable for support vector machines models, but classification trees achieved better results using original data. … celý popis

Podrobná bibliografie

Hlavní autor

Michaela Stanková

Další autoři

David Hampel, 1978-

Typ dokumentu

Články

Fyzický popis

5 ilustrací

Publikováno v

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis. -- ISSN 1211-8516. -- Roč. 66, č. 5 (2018), s. 1347-1356

Témata

EUROPEAN UNION

small and medium enterprises

Companies

CLASSIFICATION

STATISTICAL METHODS

Regression analysis

bankruptcy

Artificial intelligence

MATHEMATICAL MODELS

Evropská unie

malé a střední podniky

společnosti

klasifikace

statistické metody

regresní analýza

prognózování

umělá inteligence

matematické modely

strojové učení > podpůrné vektorové stroje > klasifikační a regresní stromy > binární klasifikace

Popis jednotky

2 grafy, 3 tabulky

Bibliografie

Seznam literatury na s. 1355-1356,