Small business credit scoring: A comparison of logistic regression, neural network and decision tree models (CROSBI ID 504081)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Zekić-Sušac, Marijana ; Šarlija, Nataša ; Benšić, Mirta
engleski
Small business credit scoring: A comparison of logistic regression, neural network and decision tree models
The paper compares the models for small business credit scoring developed by logistic regression, neural networks, and CART decision trees on a Croatian bank dataset. The models obtained by all three methodologies were estimated ; then validated on the same hold-out sample, and their performance is compared. There is an evident significant difference among the best neural network model, decision tree model, and logistic regression model. The most successful neural network model was obtained by the probabilistic algorithm. The best model extracted the most important features for small business credit scoring from the observed data.
credit scoring modeling; decision trees; logistic regression; neural network; small business
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Podaci o prilogu
265-270-x.
2004.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 26th International Conference on Information Tehnology Interfaces
Lužar-Stiffler, Vesna
Zagreb: Sveučilišni računski centar Sveučilišta u Zagrebu (Srce)
Podaci o skupu
International Conference on Information Technology Interfaces (ITI) 2004
predavanje
07.06.2004-10.06.2004
Dubrovnik, Hrvatska; Cavtat, Hrvatska