[Title:] Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Dubrovnik, Croatia, 7-9 September 2017 [ISSN:] 2706-4735 [Volume:] 3 [Pages:] 88-93
The goal of the paper is to present the overview of methodology of using credit scoring analysis with software Weka. German credit dataset was used in order to develop a decision tree with J.48 algorithm. We present characteristics of the dataset and the main results with the focus to the interpretation of Weka output. Paper could be useful for the users of Weka that aim to use it for credit scoring analysis.
data base credit risk data mining knowledge discovery granting credits