Enhancements on local outlier detection

Outliers, commonly referred to as exceptional cases, exist in many real-world databases. Detection of such outliers is important for many applications. In this paper, we focus on the density-based notion that discovers local outliers by means of the local outlier factor (LOF) formulation. Three enhancement schemes over LOF are introduced, namely LOF' and LOF" and GridLOF. Thorough explanation and analysis is given to demonstrate the abilities of LOF' in providing simpler and more intuitive meaning of local outlier-ness; LOF" in handling cases where LOF fails to work appropriately; and GridLOF in improving the efficiency and accuracy.