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An iterative bootstrapping-based data over-sampling strategy is presented in this paper together with an adaptive neural-fuzzy inference system (ANFIS) to deal with a severely imbalanced data modelling problem. As real industrial data are often very large, containing hundreds of process variables and a huge number of data records, the selection of a compact set of input variables becomes critical...
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