Adrian Bona

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Current important challenges in data mining research are triggered by the need to address various particularities of real-world problems, such as imbalanced data and error cost distributions. This paper presents Distributed Evolutionary Cost-Sensitive Balancing, a distributed methodology for dealing with imbalanced data and -- if necessary -- cost(More)
Imbalanced classification problems represent a current challenge in data mining research, due to the classifiers' inability to produce sufficiently good models in such situations. We have previously proposed a general methodology for improving the performance of classifiers under imbalance conditions: ECSB -- Evolutionary Cost-Sensitive Balancing. This(More)
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