NAÏVE BAYES AS A MEANS OF CONSTRUCTING APPLICATION SCORECARDS

Anthony C. Antonakis and Michael E. Sfakianakis
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Anthony C. Antonakis: University of Piraeus, Greece
Michael E. Sfakianakis: University of Piraeus, Greece

Chapter 3 in Advances in Doctoral Research in Management, 2008, pp 47-61 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractThis study examines the effectiveness of the Naïve Bayes Rule relative to that of five other popular algorithms in constructing scorecards that correctly discriminate between good-risk and bad-risk credit applicants. Scorecard performance is assessed on a real-world data sample by both the percentage of correctly classified cases and the more relevant criterion of bad rate among accepts. Naive Bayes is found to produce the worst-performing scorecard under both measures used.

Keywords: Doctoral; Research; Management Methodology; Data; Analysis; Paradigm; Modeling; International; Management Theory; Statistics; Market Survey (search for similar items in EconPapers)
JEL-codes: F1 (search for similar items in EconPapers)
Date: 2008
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