297 Copyright © 2010, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 18 The Power of Sampling and Stacking for the PAKDD-2007 Cross-Selling Problem Paulo J.L. Adeodato NeuroTech Ltd. and Federal University of Pernambuco, Brazil Germano C. Vasconcelos NeuroTech Ltd. and Federal University of Pernambuco, Brazil Adrian L. Arnaud NeuroTech Ltd. and Federal University of Pernambuco, Brazil Rodrigo C.L.V. Cunha NeuroTech Ltd. and Federal University of Pernambuco, Brazil Domingos S.M.P. Monteiro NeuroTech Ltd. and Federal University of Pernambuco, Brazil Rosalvo F. Oliveira Neto NeuroTech Ltd. and Federal University of Pernambuco, Brazil abstract This article presents an effcient solution for the PAKDD-2007 Competition cross-selling problem. The solution is based on a thorough approach which involves the creation of new input variables, effcient data preparation and transformation, adequate data sampling strategy and a combination of two of the most robust modeling techniques. Due to the complexity imposed by the very small amount of examples in the target class, the approach for model robustness was to produce the median score of the 11 models developed with an adapted version of the 11-fold cross-validation process and the use of a combination of two robust techniques via stacking, the MLP neural network and the n-tuple classifer. Despite the problem complexity, the performance on the prediction data set (unlabeled samples), measured through KS2 and ROC curves was shown to be very effective and fnished as the frst runner-up solution of the competition.