Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/183764 
Erscheinungsjahr: 
2017
Quellenangabe: 
[Title:] Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Dubrovnik, Croatia, 7-9 September 2017 [Publisher:] IRENET - Society for Advancing Innovation and Research in Economy [Place:] Zagreb [Year:] 2017 [Pages:] 88-93
Verlag: 
IRENET - Society for Advancing Innovation and Research in Economy, Zagreb
Zusammenfassung: 
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.
Schlagwörter: 
data base
credit risk
data mining
knowledge discovery
granting credits
JEL: 
D81
C80
Creative-Commons-Lizenz: 
cc-by-nc Logo
Dokumentart: 
Conference Paper

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