Abstract
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.
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Gupta, U., Bhattacharjee, V., Bishnu, P.S. (2019). A New Neighborhood-Based Outlier Detection Technique. In: Nath, V., Mandal, J. (eds) Proceedings of the Third International Conference on Microelectronics, Computing and Communication Systems. Lecture Notes in Electrical Engineering, vol 556. Springer, Singapore. https://doi.org/10.1007/978-981-13-7091-5_43
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DOI: https://doi.org/10.1007/978-981-13-7091-5_43
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