This paper demonstrates that if the goal of modeling is prediction, with a large number of covariates and little theoretical guidance for choosing among them, the approach based on the combination of stepwise logistic regression, information criteria, and best subset selection will result in fully automated procedure (due to ODS). The approach inherits the best features of the three components mentioned in this paper and helps to avoid an agonizing process of choosing the "Right" critical p-value. If the approach is applied to Enterprise Miner, one can strengthen the Regression node in comparison with other modeling nodes (the Neural Network and Tree).
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