中文摘要：

孤立点检测是数据挖掘的重要研究方向之一，目标是发现数据集中不具备数据一般特性的数据对象．通过挖掘数据属性间内在的数量关联规则，标记产生的弱关联规则中置信度小于阈值的极小概率事件为孤立点，提出了一种基于数量关联的离群点检测算法．实例表明，算法能够有效检测数据集中的孤立点，具有应用价值．

英文摘要：

Outlier detection, aim of research aspect in the data mining. which is to discover the abnormal data objects in the data set, is an important This paper proposes a new association rules between the data attributes. The outliers method to detect outliers by discovering quantitative are defined as the small probability events which confidence less than the threshold in weak association rules. Experimental results show that the algorithm can effectively on outlier detection and has some application prospect.