Abstract
Finding the best possible subset of variables to put in a model has been a frustrating exercise. Many methods of variable selection exist, but none of them is perfect. Moreover, they do not create new variables which would enhance the predictive power of the original variables themselves. Furthermore, none use a criterion that addresses the specific needs of direct marketing models. After repeated testing, the author has developed a new methodology that uses genetic modelling to find the variables of significance to direct marketers.
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Ratner, B. Finding the best variables for direct marketing models. J Target Meas Anal Mark 9, 270–296 (2001). https://doi.org/10.1057/palgrave.jt.5740021
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DOI: https://doi.org/10.1057/palgrave.jt.5740021