Consumer credit risk: Individual probability estimates using machine learning

Expert Systems with Applications

Volumn 40, Issue 13, 2013, Pages 5125-5131

  Kruppa, Jochen ^a   Schwarz, Alexandra ^b   Arminger, Gerhard ^b   Ziegler, Andreas ^a  

^a UNIVERSITY OF LÜBECK   (Germany)

^b UNIVERSITY OF WUPPERTAL   (Germany)

Author keywords

Credit scoring; Logistic regression; Machine learning; Probability estimation; Probability machines; Random forest

Indexed keywords

ARTIFICIAL INTELLIGENCE; C++ (PROGRAMMING LANGUAGE); DECISION TREES; MOTION COMPENSATION; NEAREST NEIGHBOR SEARCH; PROBABILITY; REGRESSION ANALYSIS; RISK ASSESSMENT; RISK PERCEPTION;

CREDIT SCORING; K NEAREST NEIGHBOR (KNN); LOGISTIC REGRESSION MODELING; LOGISTIC REGRESSIONS; MACHINE LEARNING METHODS; NON-PARAMETRIC REGRESSION; PROBABILITY ESTIMATION; RANDOM FORESTS;

LEARNING SYSTEMS;

EID: 84878300417     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2013.03.019     Document Type: Article

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