Evolving Bayesian classifiers for credit control – a comparison with other machine-learning methods

Evolving Bayesian classifiers for credit control – a comparison with other machine-learning methods

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Article ID: iaor2002782
Country: United Kingdom
Volume: 5
Issue: 1
Start Page Number: 63
End Page Number: 75
Publication Date: Jan 1993
Journal: IMA Journal of Mathematics Applied in Business and Industry
Authors: ,
Keywords: credit scoring, genetic algorithms
Abstract:

A machine-learning approach that uses the genetic algorithm to optimize a Bayesian classfier from a set of examples is introduced. The IDIOMS system – which has been built to support this approach as well as to allow the incorporation of human expertise into the decision process – is described, and results of using the approach in a tenfold cross-validation comparison with other machine-learning approaches on 51,023 examples of credit-card applications are presented.

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