A New Neighborhood-Based Outlier Detection Technique

Outlier detection is one of the most vital and essential issues in data mining tasks. We propose a new method to detect and analyze outliers. We apply neighborhood-based outlier detection technique to detect and analyze the outliers. Using weights of the neighbors of each data and a unique parameter OBN is used to identify the outlier. Our proposed algorithm is tested on real datasets and compared with the existing technique and the results are presented.