期刊论文详细信息
Journal of Computer Science | |
Fast Algorithms for Outlier Detection | Science Publications | |
Ali Al-Dahoud1  Fawaz A.M. Masoud1  Moh'd B. Al- Zoubi1  Imad Salah1  | |
关键词: Outlier detection; K-Nearest Neighbour (KNN); partial distance; data mining; | |
DOI : 10.3844/jcssp.2008.129.132 | |
学科分类:计算机科学(综合) | |
来源: Science Publications | |
【 摘 要 】
Finding fast algorithms to detect outliers (as unusual objects) by their distance to neighboring objects is a big desire. Two algorithms were proposed to detect outliers quickly. The first was based on the Partial Distance (PD) algorithm and the second was an improved version of the PD algorithm. It was found that the proposed algorithms reduced the number of distance calculations compared to the nested-loop method.
【 授权许可】
Unknown
【 预 览 】
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