In classification tasks, class-modular strategy has been widely used. It has outperformed classical strategy for pattern classification task in many applications [1]. However, in ...
In recent years, mining with imbalanced data sets receives more and more attentions in both theoretical and practical aspects. This paper introduces the importance of imbalanced da...
Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
This paper presents a new learning approach for pattern classification applications involving imbalanced data sets. In this approach, a clustering technique is employed to resamp...
Giang Hoang Nguyen, Abdesselam Bouzerdoum, Son Lam...