Ensembles for unsupervised outlier detection 论文
2014ACM SIGKDD Explorations Newsletter引用 270
Anomaly Detection Techniques and ApplicationsData-Driven Disease SurveillanceArtificial Immune Systems Applications
摘要
Ensembles for unsupervised outlier detection is an emerging topic that has been neglected for a surprisingly long time (although there are reasons why this is more difficult than supervised ensembles or even clustering ensembles). Aggarwal recently discussed algorithmic patterns of outlier detection ensembles, identified traces of the idea in the literature, and remarked on potential as well as unlikely avenues for future transfer of concepts from supervised ensembles. Complementary to his points, here we focus on the core ingredients for building an outlier ensemble, discuss the first steps taken in the literature, and identify challenges for future research.