Classifying imbalanced dataset based on minority detection

Classifying imbalanced dataset has recently become an important problem in many industrial and financial applications. In this paper, a novel method for combing minority detection algorithm and solving optimization problem to classify imbalanced dataset was presented. We empirically evaluate the proposed approach using a number of UCI datasets, and experiment results show that our novel method is superior to the state-of-the-art methods in the literature and scales well to large, high dimensional databases.