LOADED: Link-Based Outlier and Anomaly Detection in Evolving Data Sets
Amol Ghoting, Matthew Eric Otey, Srinivasan Parthasarathy · 2005
In this paper, we present LOADED, an algorithm for outlier detection in evolving data sets containing both continuous and categorical attributes. LOADED is a tunable algorithm, wherein one can trade off computation for accuracy so that domain-specific response times are achieved. Experimental results show that LOADED provides very good detection and false positive rates, which are several times better than those of existing distance-based schemes.