Rodrigo C. L. V. Cunha

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Neural networks and logistic regression have been among the most widely used AI techniques in applications of pattern clussiftiution. MLK~ has been discrlssed about if there is any signzficunt d&erence in between them but much less has been actually done with real-world applications data (large scale) to help settle this mutter, with a few exceptions. This(More)
abstract This article presents an efficient 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, efficient data preparation and transformation, adequate data sampling strategy and a combination of two of the most robust modeling techniques. Due to the(More)
The objective of this paper is providing an integrated environment for knowledge reuse in KDD, for preventing recurrence of known errors and reinforcing project successes, based on previous experience. It combines methodologies from project management, data warehousing, mining and knowledge representation. Different from purely algorithmic papers, this one(More)
This work presents an award winning approach for solving the NN3 Forecasting Competition problem. It consisted of predicting 18 future values of 111 monthly short time series. This approach consists of applying the median value of a 15-MLP ensemble for predicting each time series. The system performed very well on test data, finishing as the second best(More)
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