Classification rule mining for automatic credit approval using genetic programming

Mark Sinclair, Sum Sakprasat

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

27 Citations (Scopus)


Automatic credit approval is important for the efficient processing of credit applications. Eight different genetic programming (GP) approaches for the classification rule mining of a credit card application dataset are investigated, using both a Booleanizing technique and strongly- typed GP. In addition, the use of GP for missing value handling is evaluated. Overall, on the Australian Credit Approval dataset, those GP approaches that had poorer classification correctness on the training data often proved better at generalizing for the test set.
Original languageEnglish
Title of host publication2007 IEEE Congress on Evolutionary Computation
Publication statusPublished - Sept 2007


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