Nelson F. F. Ebecken

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Multilayer perceptrons adjust their internal parameters performing vector mappings from the input to the output space. Although they may achieve high classification accuracy, the knowledge acquired by such neural networks is usually incomprehensible for humans. This fact is a major obstacle in data mining applications, in which ultimately understandable(More)
In the last few years, the data mining community has proposed a number of objective rule interestingness measures to select the most interesting rules, out of a large set of discovered rules. However, it should be recalled that objective measures are just an estimate of the true degree of interestingness of a rule to the user, the so-called real human(More)
Data mining on large databases has been a major concern in research community, due to the di culty of analyzing huge volumes of data using only traditional OLAP tools. This sort of process implies a lot of computational power, memory and disk I/O, which can only be provided by parallel computers. We present a discussion of how database technology can be(More)
Cardiovascular Disease (CVD) is the single largest killer in the world. Although, several CVD treatment guidelines have been developed to improve quality of care and reduce healthcare costs, for a number of reasons, adherence to these guidelines remains poor. Further, due to the extremely poor quality of data in medical patient records, most of today’s(More)
Uncertainty assessment in basin modeling and reservoir characterization is traditionally treated by geostatistical methods which are normally based on stochastic probabilistic approaches. In this talk, an alternative interval-based approach will be present. A solution for the transient heat conduction in sedimentary basins will be introduced using an(More)