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In the field of imbalance learning and cost sensitive learning, minimization of the classification error rate is not an appropriate approach due to class skew and cost distributions. Thus the area under the ROC Curve (AUC) has been widely utilized to assess the performance of the classifiers in such cases. The Maximum AUC Linear Classifier (MALC), aiming at maximizing AUC directly, is a nonparametric...
Class imbalance learning is an important research area in machine learning, where instances in some classes heavily outnumber the instances in other classes. This unbalanced class distribution causes performance degradation. Some ensemble solutions have been proposed for the class imbalance problem. Diversity has been proved to be an influential aspect in ensemble learning, which describes the degree...
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