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Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
The class imbalance problem (when one of the classes has much less samples than the others) is of great importance in machine learning, because it corresponds to many critical app...
Abstract. One of the more challenging problems faced by the data mining community is that of imbalanced datasets. In imbalanced datasets one class (sometimes severely) outnumbers t...
In a concept learning problem, imbalances in the distribution of the data can occur either between the two classes or within a single class. Yet, although both types of imbalances ...
Abstract—This paper introduces and compares some techniques used to predict the student performance at the university. Recently, researchers have focused on applying machine lear...
Nguyen Thai-Nghe, Andre Busche, Lars Schmidt-Thiem...