generAlizeD ADDitive MoDel AnD ApplicAtionS in Direct MArketing
نویسنده
چکیده
Logistic regression1 has been widely used in direct marketing applications to develop response and conversion models. Although attractively simple, logistic regression has been criticized for failing to capture the nonlinearity, and therefore possibly not leading to satisfactory results. Introduced by Hastie and Tibshirani, Generalized Additive Model2 (GAM) provides the ability to detect the nonlinear relationship between the response behavior and predictors.
منابع مشابه
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