ADD: a new average divergence difference-based outlier detection method with skewed distribution of data objects

Outlier detection is of vital importance in data mining tasks, with numerous applications, including video surveillance and credit card fraud detection. Quite a few outlier detection algorithms have been developed and have received considerable attention, and most existing methods are classified as distance-based algorithms and density-based algorithms. However, both of these approaches have some flaws. The former has difficulty detecting local...