Direct mail is a typical example for response modeling to be used.In order to decide which people will receive the mailing,the potential customers are divided into two groups or classes (buyers and non-buyers) and a response model is created.Since the improvement of response modeling is the purponse of this paper,we suggest a combined approach of rule-induction and case-based reasoning.The initial classification of buyers and non-buyers is done by means of the C5-algorithm.To improve the ranking of the classified cases,we introduce in this research rule-predicted typicality.The combination of these two approaches is tested on synergy by elaborating a direct mail example.
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