Data Mining on Imbalanced Data Sets
用于不均衡数据集的挖掘方法

The majority of machine learning algorithms previously designed usually assume that their training sets are well-balanced,but data in real-world is usually imbalanced.The tradition machine learning algorithms on balanced data sets have bad performance when they learn from imbalaneed data sets.Thus,machine learning on imbalanced data sets becomes an urgent problem.In this paper,a simple review of the related work is informed.