DistanceBased Outlier Detection: Consolidation and Renewed Bearing

Download Now Date Added: Aug 2010
Format: PDF

Detecting outliers in data is an important problem with interesting applications in a myriad of domains ranging from data cleaning to financial fraud detection and from network intrusion detection to clinical diagnosis of diseases. Over the last decade of research, distance-based outlier detection algorithms have emerged as a viable, scalable, parameter-free alternative to the more traditional statistical approaches. In this paper the authors assess several distance-based outlier detection approaches and evaluate them.