Comparative Study of Various Techniques on Outlier Detection

Diverse patterns from web data, commonly referred to as web outliers or exceptional cases or noise; exist in many real-world databases. Detection of such outliers is important for numerous applications, such as detecting criminal activities in E-commerce. Outliers are data objects with different characteristics compared to other data objects. Formal definition of outliers is given by D.Hawkins. as “An Outlier is an observation that deviates so much from other observations so that it arouses suspicion that it is generated by a different mechanism”. Detection of such outliers (outlier mining) is important for numerous applications, such as detecting criminal activities in E-commerce, video surveillance, weather prediction, intrusion detection and pharmaceutical research. This paper has focus on comparative study of various techniques on Outlier Detection.