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Scholars Journal of Engineering and Technology | Volume-3 | Issue-06
An outlier detection algorithm based on clustering
Hongbo Zhou, Bingbing xu, Juntao Gao
Published: June 22, 2015 |
188
101
DOI: 10.36347/sjet
Pages: 595-599
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Abstract
Outlier detection is a very important type of data mining, which is extensively used in application areas. The
traditional cell-based outlier detection algorithm not only takes a large amount of time in processing massive data, but
also uses lots of machine resources, which results in the imbalance of the machine load. This paper presents an distancebased outlier detection algorithm. These experiments show that this improved algorithm is able to effectively improve the
efficiency of the outlier detection as well as the accuracy.