An Evaluation ofDetection of Outliersby Reverse Nearest Neighbors Method

Abstract

Outlier Detection in high dimensional information goes into a rising system in today’s inspection in the region of data mining.Data that is different or erratic from normal data set are recognized by outlier detection. Unusual data records because of some data errors can be treated as outliers typically detecting outliers and investigating large data sets recognizes the problem such as medical problems, a structural defect, and investigational errors. This paper focuses the different methods for detection of anomalies. In order to handle the difficulties related to outlier detection because of uncertain data, outlier detection technique based on the AntiHub term is used.