基于可达邻域的异常检测算法  

Outlier Detection Algorithm Based on Reachable Neighbor

作　　者：肖辉[1] 龚薇[2] 

机构地区：[1]浙江大学宁波理工学院,宁波315100 [2]宁波大学商学院,宁波315211

出　　处：《计算机工程》2007年第17期74-76,共3页Computer Engineering

基　　金：浙江大学宁波理工学院人才引进基金(1140157G604);宁波市自然科学基金(2007A610043)

摘　　要：提出了可达邻域的概念,定义了基于可达邻域的异常RN-Outlier。给出了RNOF异常检测算法,克服了异常检测算法常被参数依赖和参数扰动所困扰的缺点。仿真数据集和真实数据集的实验表明,该算法的性能超过了经典的LOF和LSC算法,降低了参数依赖和参数扰动的影响。Most outlier detection approaches suffer from parameter dependencies and parameter instability. In order to solve the two problems, this paper introduces a new notion of outlier based on reachable neighbor, which is called RN-Outlier, and proposes novel and fast algorithms for outlier detection. Experimental results of synthetic datasets and real datasets show that the algorithm outperforms both LOF and LSC methods. The algorithm is more stable when parameter changes.

关 键 词：异常检测 可达邻域 局域密度 局部异常 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]